Overview

Dataset statistics

Number of variables59
Number of observations500000
Missing cells3765222
Missing cells (%)12.8%
Total size in memory228.9 MiB
Average record size in memory480.0 B

Variable types

Text42
Numeric14
Unsupported3

Alerts

Visualizaciones del Procedimiento has constant value ""Constant
Proveedores que Manifestaron Interes has constant value ""Constant
Subtipo de Contrato has constant value ""Constant
Nombre del Procedimiento has 5523 (1.1%) missing valuesMissing
Descripción del Procedimiento has 11332 (2.3%) missing valuesMissing
Fecha de Publicacion (Fase Planeacion Precalificacion) has 500000 (100.0%) missing valuesMissing
Fecha de Publicacion (Fase Seleccion Precalificacion) has 500000 (100.0%) missing valuesMissing
Fecha de Publicacion (Manifestacion de Interes) has 495551 (99.1%) missing valuesMissing
Fecha de Publicacion (Fase Borrador) has 488960 (97.8%) missing valuesMissing
Fecha de Publicacion (Fase Seleccion) has 15970 (3.2%) missing valuesMissing
Fecha de Recepcion de Respuestas has 423715 (84.7%) missing valuesMissing
Fecha de Apertura de Respuesta has 442953 (88.6%) missing valuesMissing
Fecha de Apertura Efectiva has 424864 (85.0%) missing valuesMissing
Fecha Adjudicacion has 454018 (90.8%) missing valuesMissing
Precio Base is highly skewed (γ1 = 254.1476829)Skewed
Duracion is highly skewed (γ1 = 415.6958572)Skewed
Proveedores con Invitacion Directa is highly skewed (γ1 = 48.52504936)Skewed
Respuestas al Procedimiento is highly skewed (γ1 = 26.65565655)Skewed
Respuestas Externas is highly skewed (γ1 = 83.93595492)Skewed
Conteo de Respuestas a Ofertas is highly skewed (γ1 = 123.8939561)Skewed
Proveedores Unicos con Respuestas is highly skewed (γ1 = 27.83566374)Skewed
Numero de Lotes is highly skewed (γ1 = 57.74482832)Skewed
Valor Total Adjudicacion is highly skewed (γ1 = 707.1053096)Skewed
Fecha de Publicacion (Fase Planeacion Precalificacion) is an unsupported type, check if it needs cleaning or further analysisUnsupported
Fecha de Publicacion (Fase Seleccion Precalificacion) is an unsupported type, check if it needs cleaning or further analysisUnsupported
Codigo Entidad is an unsupported type, check if it needs cleaning or further analysisUnsupported
Precio Base has 12328 (2.5%) zerosZeros
Duracion has 29835 (6.0%) zerosZeros
Proveedores Invitados has 424504 (84.9%) zerosZeros
Proveedores con Invitacion Directa has 495371 (99.1%) zerosZeros
Visualizaciones del Procedimiento has 500000 (100.0%) zerosZeros
Proveedores que Manifestaron Interes has 500000 (100.0%) zerosZeros
Respuestas al Procedimiento has 445072 (89.0%) zerosZeros
Respuestas Externas has 498745 (99.7%) zerosZeros
Conteo de Respuestas a Ofertas has 498950 (99.8%) zerosZeros
Proveedores Unicos con Respuestas has 445958 (89.2%) zerosZeros
Numero de Lotes has 489486 (97.9%) zerosZeros
Valor Total Adjudicacion has 454317 (90.9%) zerosZeros

Reproduction

Analysis started2024-01-12 01:39:56.253094
Analysis finished2024-01-12 01:40:48.054718
Duration51.8 seconds
Software versionydata-profiling vv4.6.4
Download configurationconfig.json

Variables

Distinct8243
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:48.225838image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length150
Median length102
Mean length39.604066
Min length3

Characters and Unicode

Total characters19802033
Distinct characters83
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1403 ?
Unique (%)0.3%

Sample

1st rowAGENCIA NACIONAL DE TIERRAS ANT
2nd rowINSTITUTO COLOMBIANO AGROPECUARIO ICA
3rd rowFONDANE DIRECCION TERRITORIAL CENTRO
4th rowEMPRESA DE VIVIENDA Y DESARROLLO URBANO Y RURAL DEL MUNICIPIO DE ENVIGADO
5th rowDIGSA
ValueCountFrequency (%)
de 424811
 
15.4%
del 90182
 
3.3%
y 62409
 
2.3%
la 53851
 
2.0%
ese 50528
 
1.8%
municipio 49942
 
1.8%
hospital 47625
 
1.7%
instituto 38389
 
1.4%
regional 34150
 
1.2%
distrital 33569
 
1.2%
Other values (5404) 1869676
67.9%
2024-01-11T20:40:48.534995image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2320911
11.7%
A 2151609
 
10.9%
E 1830625
 
9.2%
I 1741778
 
8.8%
O 1178400
 
6.0%
N 1133394
 
5.7%
D 1100079
 
5.6%
R 1031573
 
5.2%
C 951807
 
4.8%
T 932790
 
4.7%
Other values (73) 5429067
27.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 16367868
82.7%
Space Separator 2320911
 
11.7%
Lowercase Letter 1100135
 
5.6%
Decimal Number 13119
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 2151609
13.1%
E 1830625
11.2%
I 1741778
10.6%
O 1178400
 
7.2%
N 1133394
 
6.9%
D 1100079
 
6.7%
R 1031573
 
6.3%
C 951807
 
5.8%
T 932790
 
5.7%
S 931320
 
5.7%
Other values (27) 3384493
20.7%
Lowercase Letter
ValueCountFrequency (%)
i 133431
12.1%
a 119870
10.9%
r 110335
10.0%
o 100603
9.1%
t 99688
9.1%
e 95676
8.7%
n 73295
 
6.7%
d 55986
 
5.1%
c 53081
 
4.8%
l 46642
 
4.2%
Other values (25) 211528
19.2%
Decimal Number
ValueCountFrequency (%)
1 6551
49.9%
2 1841
 
14.0%
6 1127
 
8.6%
4 747
 
5.7%
3 622
 
4.7%
8 529
 
4.0%
7 512
 
3.9%
5 491
 
3.7%
0 407
 
3.1%
9 292
 
2.2%
Space Separator
ValueCountFrequency (%)
2320911
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17468003
88.2%
Common 2334030
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 2151609
12.3%
E 1830625
10.5%
I 1741778
 
10.0%
O 1178400
 
6.7%
N 1133394
 
6.5%
D 1100079
 
6.3%
R 1031573
 
5.9%
C 951807
 
5.4%
T 932790
 
5.3%
S 931320
 
5.3%
Other values (62) 4484628
25.7%
Common
ValueCountFrequency (%)
2320911
99.4%
1 6551
 
0.3%
2 1841
 
0.1%
6 1127
 
< 0.1%
4 747
 
< 0.1%
3 622
 
< 0.1%
8 529
 
< 0.1%
7 512
 
< 0.1%
5 491
 
< 0.1%
0 407
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19650656
99.2%
None 151377
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2320911
11.8%
A 2151609
10.9%
E 1830625
 
9.3%
I 1741778
 
8.9%
O 1178400
 
6.0%
N 1133394
 
5.8%
D 1100079
 
5.6%
R 1031573
 
5.2%
C 951807
 
4.8%
T 932790
 
4.7%
Other values (53) 5277690
26.9%
None
ValueCountFrequency (%)
Ó 52583
34.7%
Í 31218
20.6%
ó 15703
 
10.4%
Ñ 12991
 
8.6%
Á 12393
 
8.2%
í 11510
 
7.6%
Ú 5196
 
3.4%
É 2991
 
2.0%
á 2603
 
1.7%
Ò 1663
 
1.1%
Other values (10) 2526
 
1.7%

Nit Entidad
Real number (ℝ)

Distinct8229
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1586568901
Minimum1
Maximum9876543210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:48.621255image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile800104062
Q1830115395
median891280000
Q3899999239
95-th percentile8909807673
Maximum9876543210
Range9876543209
Interquartile range (IQR)69883844

Descriptive statistics

Standard deviation2265322274
Coefficient of variation (CV)1.427812099
Kurtosis6.148296306
Mean1586568901
Median Absolute Deviation (MAD)8754608
Skewness2.848245207
Sum7.932844507 × 1014
Variance5.131685003 × 1018
MonotonicityNot monotonic
2024-01-11T20:40:48.695057image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
899999034 16951
 
3.4%
899999061 14773
 
3.0%
8999990619 12954
 
2.6%
890399011 12606
 
2.5%
899999239 6877
 
1.4%
899999027 6183
 
1.2%
900971006 5764
 
1.2%
899999063 4174
 
0.8%
899999114 3479
 
0.7%
891480030 3276
 
0.7%
Other values (8219) 412963
82.6%
ValueCountFrequency (%)
1 1
 
< 0.1%
4653184 9
 
< 0.1%
7180873 3
 
< 0.1%
63545111 4
 
< 0.1%
80864049 227
< 0.1%
ValueCountFrequency (%)
9876543210 1
 
< 0.1%
9016759395 1
 
< 0.1%
9016289940 6
< 0.1%
9016130902 1
 
< 0.1%
9015641901 7
< 0.1%
Distinct34
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:48.925068image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length40
Median length26
Mean length13.515058
Min length4

Characters and Unicode

Total characters6757529
Distinct characters45
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDistrito Capital de Bogotá
2nd rowDistrito Capital de Bogotá
3rd rowDistrito Capital de Bogotá
4th rowAntioquia
5th rowDistrito Capital de Bogotá
ValueCountFrequency (%)
no 156684
14.6%
definido 156684
14.6%
de 109900
10.2%
distrito 104130
9.7%
capital 104130
9.7%
bogotá 104130
9.7%
antioquia 43454
 
4.0%
cauca 41528
 
3.9%
valle 35058
 
3.3%
del 35058
 
3.3%
Other values (35) 185504
17.2%
2024-01-11T20:40:49.135280image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 788979
11.7%
o 741001
 
11.0%
a 629241
 
9.3%
576260
 
8.5%
t 529737
 
7.8%
e 392133
 
5.8%
d 376160
 
5.6%
n 320573
 
4.7%
l 268703
 
4.0%
D 260814
 
3.9%
Other values (35) 1873928
27.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5249967
77.7%
Uppercase Letter 926640
 
13.7%
Space Separator 576260
 
8.5%
Other Punctuation 4662
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 788979
15.0%
o 741001
14.1%
a 629241
12.0%
t 529737
10.1%
e 392133
7.5%
d 376160
7.2%
n 320573
 
6.1%
l 268703
 
5.1%
r 198253
 
3.8%
f 156684
 
3.0%
Other values (18) 848503
16.2%
Uppercase Letter
ValueCountFrequency (%)
D 260814
28.1%
C 185312
20.0%
N 169690
18.3%
B 123450
13.3%
A 67967
 
7.3%
V 36294
 
3.9%
S 32003
 
3.5%
M 12678
 
1.4%
P 7687
 
0.8%
T 7306
 
0.8%
Other values (5) 23439
 
2.5%
Space Separator
ValueCountFrequency (%)
576260
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4662
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6176607
91.4%
Common 580922
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 788979
12.8%
o 741001
12.0%
a 629241
 
10.2%
t 529737
 
8.6%
e 392133
 
6.3%
d 376160
 
6.1%
n 320573
 
5.2%
l 268703
 
4.4%
D 260814
 
4.2%
r 198253
 
3.2%
Other values (33) 1671013
27.1%
Common
ValueCountFrequency (%)
576260
99.2%
, 4662
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6594618
97.6%
None 162911
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 788979
12.0%
o 741001
11.2%
a 629241
 
9.5%
576260
 
8.7%
t 529737
 
8.0%
e 392133
 
5.9%
d 376160
 
5.7%
n 320573
 
4.9%
l 268703
 
4.1%
D 260814
 
4.0%
Other values (30) 1711017
25.9%
None
ValueCountFrequency (%)
á 128740
79.0%
í 16773
 
10.3%
ñ 7236
 
4.4%
ó 5189
 
3.2%
é 4973
 
3.1%
Distinct944
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:49.311324image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length8.63945
Min length3

Characters and Unicode

Total characters4319725
Distinct characters58
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)< 0.1%

Sample

1st rowBogotá
2nd rowBogotá
3rd rowBogotá
4th rowRionegro
5th rowBogotá
ValueCountFrequency (%)
no 175875
24.5%
definido 175875
24.5%
bogotá 88573
12.3%
cali 26092
 
3.6%
medellín 24388
 
3.4%
san 11876
 
1.7%
bucaramanga 7650
 
1.1%
cartagena 7017
 
1.0%
santa 6768
 
0.9%
arauca 6725
 
0.9%
Other values (934) 187202
26.1%
2024-01-11T20:40:49.562133image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 622239
14.4%
i 457766
 
10.6%
e 324589
 
7.5%
a 315849
 
7.3%
n 309610
 
7.2%
d 233322
 
5.4%
218041
 
5.0%
D 183590
 
4.3%
N 180606
 
4.2%
f 176831
 
4.1%
Other values (48) 1297282
30.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3383643
78.3%
Uppercase Letter 718041
 
16.6%
Space Separator 218041
 
5.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 622239
18.4%
i 457766
13.5%
e 324589
9.6%
a 315849
9.3%
n 309610
9.2%
d 233322
 
6.9%
f 176831
 
5.2%
l 143279
 
4.2%
t 140271
 
4.1%
g 120548
 
3.6%
Other values (21) 539339
15.9%
Uppercase Letter
ValueCountFrequency (%)
D 183590
25.6%
N 180606
25.2%
B 109692
15.3%
C 49040
 
6.8%
M 45305
 
6.3%
S 31336
 
4.4%
P 28779
 
4.0%
A 24992
 
3.5%
T 9539
 
1.3%
V 7897
 
1.1%
Other values (16) 47265
 
6.6%
Space Separator
ValueCountFrequency (%)
218041
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4101684
95.0%
Common 218041
 
5.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 622239
15.2%
i 457766
 
11.2%
e 324589
 
7.9%
a 315849
 
7.7%
n 309610
 
7.5%
d 233322
 
5.7%
D 183590
 
4.5%
N 180606
 
4.4%
f 176831
 
4.3%
l 143279
 
3.5%
Other values (47) 1154003
28.1%
Common
ValueCountFrequency (%)
218041
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4163964
96.4%
None 155761
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 622239
14.9%
i 457766
11.0%
e 324589
 
7.8%
a 315849
 
7.6%
n 309610
 
7.4%
d 233322
 
5.6%
218041
 
5.2%
D 183590
 
4.4%
N 180606
 
4.3%
f 176831
 
4.2%
Other values (39) 1141521
27.4%
None
ValueCountFrequency (%)
á 101843
65.4%
í 32291
 
20.7%
é 11573
 
7.4%
ó 5123
 
3.3%
ú 3202
 
2.1%
ñ 1660
 
1.1%
ü 44
 
< 0.1%
Á 24
 
< 0.1%
Ú 1
 
< 0.1%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:49.655420image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length20
Median length11
Mean length10.080428
Min length8

Characters and Unicode

Total characters5040214
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNacional
2nd rowNacional
3rd rowNacional
4th rowTerritorial
5th rowNacional
ValueCountFrequency (%)
territorial 315073
62.0%
nacional 177007
34.8%
corporación 7915
 
1.6%
autónoma 7915
 
1.6%
no 5
 
< 0.1%
definido 5
 
< 0.1%
2024-01-11T20:40:49.813777image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 961049
19.1%
i 815078
16.2%
a 684917
13.6%
o 515835
10.2%
l 492080
9.8%
t 322988
 
6.4%
e 315078
 
6.3%
T 315073
 
6.3%
n 192842
 
3.8%
c 184922
 
3.7%
Other values (11) 240352
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4524374
89.8%
Uppercase Letter 507920
 
10.1%
Space Separator 7920
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 961049
21.2%
i 815078
18.0%
a 684917
15.1%
o 515835
11.4%
l 492080
10.9%
t 322988
 
7.1%
e 315078
 
7.0%
n 192842
 
4.3%
c 184922
 
4.1%
ó 15830
 
0.3%
Other values (5) 23755
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
T 315073
62.0%
N 177012
34.9%
C 7915
 
1.6%
A 7915
 
1.6%
D 5
 
< 0.1%
Space Separator
ValueCountFrequency (%)
7920
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5032294
99.8%
Common 7920
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 961049
19.1%
i 815078
16.2%
a 684917
13.6%
o 515835
10.3%
l 492080
9.8%
t 322988
 
6.4%
e 315078
 
6.3%
T 315073
 
6.3%
n 192842
 
3.8%
c 184922
 
3.7%
Other values (10) 232432
 
4.6%
Common
ValueCountFrequency (%)
7920
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5024384
99.7%
None 15830
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 961049
19.1%
i 815078
16.2%
a 684917
13.6%
o 515835
10.3%
l 492080
9.8%
t 322988
 
6.4%
e 315078
 
6.3%
T 315073
 
6.3%
n 192842
 
3.8%
c 184922
 
3.7%
Other values (10) 224522
 
4.5%
None
ValueCountFrequency (%)
ó 15830
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:49.883563image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1000000
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSi
2nd rowSi
3rd rowSi
4th rowSi
5th rowNo
ValueCountFrequency (%)
si 282831
56.6%
no 217169
43.4%
2024-01-11T20:40:50.003222image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 282831
28.3%
i 282831
28.3%
N 217169
21.7%
o 217169
21.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 500000
50.0%
Lowercase Letter 500000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 282831
56.6%
N 217169
43.4%
Lowercase Letter
ValueCountFrequency (%)
i 282831
56.6%
o 217169
43.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 1000000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 282831
28.3%
i 282831
28.3%
N 217169
21.7%
o 217169
21.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 282831
28.3%
i 282831
28.3%
N 217169
21.7%
o 217169
21.7%
Distinct498878
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:50.356184image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length15
Median length15
Mean length14.90334
Min length11

Characters and Unicode

Total characters7451670
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique498144 ?
Unique (%)99.6%

Sample

1st rowCO1.REQ.291333
2nd rowCO1.REQ.2538349
3rd rowCO1.REQ.1756578
4th rowCO1.REQ.4570759
5th rowCO1.REQ.3846725
ValueCountFrequency (%)
co1.req.3971836 19
 
< 0.1%
co1.req.778356 18
 
< 0.1%
co1.req.2906406 18
 
< 0.1%
co1.req.1241749 17
 
< 0.1%
co1.req.2303540 11
 
< 0.1%
co1.req.3439081 11
 
< 0.1%
co1.req.916747 9
 
< 0.1%
co1.req.3230462 9
 
< 0.1%
co1.req.3068162 9
 
< 0.1%
co1.req.2923350 9
 
< 0.1%
Other values (498868) 499870
> 99.9%
2024-01-11T20:40:50.762954image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1000000
13.4%
1 903880
12.1%
C 500000
 
6.7%
O 500000
 
6.7%
R 500000
 
6.7%
E 500000
 
6.7%
Q 500000
 
6.7%
4 415562
 
5.6%
3 415547
 
5.6%
2 413589
 
5.6%
Other values (6) 1803092
24.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3951670
53.0%
Uppercase Letter 2500000
33.5%
Other Punctuation 1000000
 
13.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 903880
22.9%
4 415562
10.5%
3 415547
10.5%
2 413589
10.5%
5 326602
 
8.3%
0 306008
 
7.7%
7 302619
 
7.7%
6 295695
 
7.5%
8 290536
 
7.4%
9 281632
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
C 500000
20.0%
O 500000
20.0%
R 500000
20.0%
E 500000
20.0%
Q 500000
20.0%
Other Punctuation
ValueCountFrequency (%)
. 1000000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4951670
66.5%
Latin 2500000
33.5%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1000000
20.2%
1 903880
18.3%
4 415562
8.4%
3 415547
8.4%
2 413589
8.4%
5 326602
 
6.6%
0 306008
 
6.2%
7 302619
 
6.1%
6 295695
 
6.0%
8 290536
 
5.9%
Latin
ValueCountFrequency (%)
C 500000
20.0%
O 500000
20.0%
R 500000
20.0%
E 500000
20.0%
Q 500000
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7451670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1000000
13.4%
1 903880
12.1%
C 500000
 
6.7%
O 500000
 
6.7%
R 500000
 
6.7%
E 500000
 
6.7%
Q 500000
 
6.7%
4 415562
 
5.6%
3 415547
 
5.6%
2 413589
 
5.6%
Other values (6) 1803092
24.2%
Distinct454614
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:51.207421image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length118
Median length112
Mean length16.931928
Min length1

Characters and Unicode

Total characters8465964
Distinct characters120
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique437908 ?
Unique (%)87.6%

Sample

1st rowCD - CPS - 031 de 2017
2nd rowSPA-DSA-VAL-1870-2021
3rd rowEDP-05-OP-2021-1BOG
4th rowDESur-CD-112-2023
5th row050- MDN-COGFM-JEMCO-DIGSA-2023
ValueCountFrequency (%)
de 53722
 
6.5%
2023 15188
 
1.8%
2022 12593
 
1.5%
presentación 12389
 
1.5%
cd 12360
 
1.5%
oferta 11744
 
1.4%
10444
 
1.3%
cuantía 9570
 
1.2%
menor 9382
 
1.1%
pn 9227
 
1.1%
Other values (407007) 669854
81.0%
2024-01-11T20:40:51.700961image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1194152
14.1%
0 976795
 
11.5%
- 967483
 
11.4%
1 471408
 
5.6%
C 405309
 
4.8%
3 355988
 
4.2%
329589
 
3.9%
S 305686
 
3.6%
D 286972
 
3.4%
P 235735
 
2.8%
Other values (110) 2936847
34.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3909198
46.2%
Uppercase Letter 2491937
29.4%
Dash Punctuation 967483
 
11.4%
Lowercase Letter 587098
 
6.9%
Space Separator 329677
 
3.9%
Other Punctuation 96432
 
1.1%
Open Punctuation 33756
 
0.4%
Close Punctuation 33743
 
0.4%
Connector Punctuation 13632
 
0.2%
Other Symbol 1744
 
< 0.1%
Other values (5) 1264
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 405309
16.3%
S 305686
12.3%
D 286972
11.5%
P 235735
9.5%
A 183680
 
7.4%
E 143562
 
5.8%
I 133807
 
5.4%
M 115753
 
4.6%
N 110153
 
4.4%
O 109562
 
4.4%
Other values (28) 461718
18.5%
Lowercase Letter
ValueCountFrequency (%)
e 95154
16.2%
n 74973
12.8%
a 67103
11.4%
t 56588
9.6%
i 46195
7.9%
r 46121
7.9%
s 34186
 
5.8%
o 31729
 
5.4%
c 26972
 
4.6%
d 26970
 
4.6%
Other values (24) 81107
13.8%
Other Punctuation
ValueCountFrequency (%)
. 89558
92.9%
/ 5386
 
5.6%
* 643
 
0.7%
, 629
 
0.7%
# 99
 
0.1%
: 36
 
< 0.1%
& 25
 
< 0.1%
% 20
 
< 0.1%
; 15
 
< 0.1%
' 14
 
< 0.1%
Other values (4) 7
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 1194152
30.5%
0 976795
25.0%
1 471408
 
12.1%
3 355988
 
9.1%
4 183961
 
4.7%
5 154321
 
3.9%
8 146859
 
3.8%
9 144091
 
3.7%
6 143320
 
3.7%
7 138303
 
3.5%
Math Symbol
ValueCountFrequency (%)
| 35
46.7%
+ 35
46.7%
< 2
 
2.7%
= 2
 
2.7%
> 1
 
1.3%
Control
ValueCountFrequency (%)
– 576
92.3%
45
 
7.2%
“ 2
 
0.3%
” 1
 
0.2%
Modifier Symbol
ValueCountFrequency (%)
´ 15
83.3%
¨ 2
 
11.1%
` 1
 
5.6%
Space Separator
ValueCountFrequency (%)
329589
> 99.9%
  88
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 33739
99.9%
[ 17
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 33726
99.9%
] 17
 
0.1%
Other Letter
ValueCountFrequency (%)
º 476
98.3%
ª 8
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 967483
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 13632
100.0%
Other Symbol
ValueCountFrequency (%)
° 1744
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5386445
63.6%
Latin 3079519
36.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 405309
 
13.2%
S 305686
 
9.9%
D 286972
 
9.3%
P 235735
 
7.7%
A 183680
 
6.0%
E 143562
 
4.7%
I 133807
 
4.3%
M 115753
 
3.8%
N 110153
 
3.6%
O 109562
 
3.6%
Other values (64) 1049300
34.1%
Common
ValueCountFrequency (%)
2 1194152
22.2%
0 976795
18.1%
- 967483
18.0%
1 471408
 
8.8%
3 355988
 
6.6%
329589
 
6.1%
4 183961
 
3.4%
5 154321
 
2.9%
8 146859
 
2.7%
9 144091
 
2.7%
Other values (36) 461798
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8415927
99.4%
None 50037
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1194152
14.2%
0 976795
 
11.6%
- 967483
 
11.5%
1 471408
 
5.6%
C 405309
 
4.8%
3 355988
 
4.2%
329589
 
3.9%
S 305686
 
3.6%
D 286972
 
3.4%
P 235735
 
2.8%
Other values (80) 2886810
34.3%
None
ValueCountFrequency (%)
ó 23307
46.6%
í 9410
18.8%
é 9243
 
18.5%
Ó 2424
 
4.8%
° 1744
 
3.5%
Ñ 944
 
1.9%
Í 854
 
1.7%
– 576
 
1.2%
º 476
 
1.0%
Ú 315
 
0.6%
Other values (20) 744
 
1.5%

PCI
Text

Distinct798
Distinct (%)0.2%
Missing1226
Missing (%)0.2%
Memory size7.6 MiB
2024-01-11T20:40:51.837945image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length41
Median length2
Mean length4.620391199
Min length1

Characters and Unicode

Total characters2304531
Distinct characters38
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)< 0.1%

Sample

1st row17-17-00
2nd row17-02-00-000
3rd row04-02-00-00F
4th rowND
5th row15-01-11-000
ValueCountFrequency (%)
nd 345184
69.1%
00-00-00 10551
 
2.1%
7 3276
 
0.7%
17-16-00 2384
 
0.5%
17-02-00-000 2345
 
0.5%
24-02-00 2321
 
0.5%
04-03-00 1805
 
0.4%
17-17-00 1748
 
0.3%
37-01-01-000 1723
 
0.3%
35-03-00 1529
 
0.3%
Other values (798) 126628
 
25.4%
2024-01-11T20:40:52.046780image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 580410
25.2%
- 395150
17.1%
D 347648
15.1%
N 345258
15.0%
1 222540
 
9.7%
2 101858
 
4.4%
3 71640
 
3.1%
5 53230
 
2.3%
4 50719
 
2.2%
6 50563
 
2.2%
Other values (28) 85515
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1203762
52.2%
Uppercase Letter 704644
30.6%
Dash Punctuation 395150
 
17.1%
Space Separator 720
 
< 0.1%
Lowercase Letter 140
 
< 0.1%
Other Punctuation 115
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 347648
49.3%
N 345258
49.0%
F 1954
 
0.3%
A 1547
 
0.2%
M 1529
 
0.2%
C 1310
 
0.2%
L 1221
 
0.2%
I 985
 
0.1%
E 957
 
0.1%
B 561
 
0.1%
Other values (8) 1674
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 580410
48.2%
1 222540
 
18.5%
2 101858
 
8.5%
3 71640
 
6.0%
5 53230
 
4.4%
4 50719
 
4.2%
6 50563
 
4.2%
7 30739
 
2.6%
8 21340
 
1.8%
9 20723
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
e 40
28.6%
r 20
14.3%
n 20
14.3%
c 20
14.3%
i 20
14.3%
a 20
14.3%
Other Punctuation
ValueCountFrequency (%)
; 75
65.2%
/ 40
34.8%
Dash Punctuation
ValueCountFrequency (%)
- 395150
100.0%
Space Separator
ValueCountFrequency (%)
720
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1599747
69.4%
Latin 704784
30.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 347648
49.3%
N 345258
49.0%
F 1954
 
0.3%
A 1547
 
0.2%
M 1529
 
0.2%
C 1310
 
0.2%
L 1221
 
0.2%
I 985
 
0.1%
E 957
 
0.1%
B 561
 
0.1%
Other values (14) 1814
 
0.3%
Common
ValueCountFrequency (%)
0 580410
36.3%
- 395150
24.7%
1 222540
 
13.9%
2 101858
 
6.4%
3 71640
 
4.5%
5 53230
 
3.3%
4 50719
 
3.2%
6 50563
 
3.2%
7 30739
 
1.9%
8 21340
 
1.3%
Other values (4) 21558
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2304531
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 580410
25.2%
- 395150
17.1%
D 347648
15.1%
N 345258
15.0%
1 222540
 
9.7%
2 101858
 
4.4%
3 71640
 
3.1%
5 53230
 
2.3%
4 50719
 
2.2%
6 50563
 
2.2%
Other values (28) 85515
 
3.7%
Distinct495959
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:52.400791image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length15.90105
Min length12

Characters and Unicode

Total characters7950525
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique492455 ?
Unique (%)98.5%

Sample

1st rowCO1.BDOS.283327
2nd rowCO1.BDOS.2462363
3rd rowCO1.BDOS.1706480
4th rowCO1.BDOS.4467257
5th rowCO1.BDOS.3751369
ValueCountFrequency (%)
co1.bdos.3875636 19
 
< 0.1%
co1.bdos.756351 18
 
< 0.1%
co1.bdos.2829403 18
 
< 0.1%
co1.bdos.1203362 17
 
< 0.1%
co1.bdos.3221288 11
 
< 0.1%
co1.bdos.2153594 11
 
< 0.1%
co1.bdos.2846850 9
 
< 0.1%
co1.bdos.3145262 9
 
< 0.1%
co1.bdos.859010 9
 
< 0.1%
co1.bdos.2986258 9
 
< 0.1%
Other values (495949) 499870
> 99.9%
2024-01-11T20:40:52.805796image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 1000000
12.6%
. 1000000
12.6%
1 902904
11.4%
C 500000
 
6.3%
B 500000
 
6.3%
D 500000
 
6.3%
S 500000
 
6.3%
3 425588
 
5.4%
4 418497
 
5.3%
2 404265
 
5.1%
Other values (6) 1799271
22.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3950525
49.7%
Uppercase Letter 3000000
37.7%
Other Punctuation 1000000
 
12.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 902904
22.9%
3 425588
10.8%
4 418497
10.6%
2 404265
10.2%
5 316750
 
8.0%
0 313176
 
7.9%
6 299927
 
7.6%
7 299283
 
7.6%
8 287270
 
7.3%
9 282865
 
7.2%
Uppercase Letter
ValueCountFrequency (%)
O 1000000
33.3%
C 500000
16.7%
B 500000
16.7%
D 500000
16.7%
S 500000
16.7%
Other Punctuation
ValueCountFrequency (%)
. 1000000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4950525
62.3%
Latin 3000000
37.7%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1000000
20.2%
1 902904
18.2%
3 425588
8.6%
4 418497
8.5%
2 404265
8.2%
5 316750
 
6.4%
0 313176
 
6.3%
6 299927
 
6.1%
7 299283
 
6.0%
8 287270
 
5.8%
Latin
ValueCountFrequency (%)
O 1000000
33.3%
C 500000
16.7%
B 500000
16.7%
D 500000
16.7%
S 500000
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7950525
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 1000000
12.6%
. 1000000
12.6%
1 902904
11.4%
C 500000
 
6.3%
B 500000
 
6.3%
D 500000
 
6.3%
S 500000
 
6.3%
3 425588
 
5.4%
4 418497
 
5.3%
2 404265
 
5.1%
Other values (6) 1799271
22.6%
Distinct321973
Distinct (%)65.1%
Missing5523
Missing (%)1.1%
Memory size7.6 MiB
2024-01-11T20:40:53.071427image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length200
Median length177
Mean length81.44882573
Min length6

Characters and Unicode

Total characters40274571
Distinct characters105
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique291940 ?
Unique (%)59.0%

Sample

1st rowJOSÉ ORLANDO CRUZ
2nd rowPrestar servicios personales de apoyo a la gestión en la Gerencia Seccional Valle del Cauca apoyando las actividades relacionadas con la expedición de Guías Sanitarias de Movilización Interna
3rd rowCONVSDDE202021LOGTHTU Prestación de servicios para coordinar los procesos preoperativos operativos de entrenamiento levantamiento de la información acompañamiento a fuentes captura y valida
4th rowSERVICIOS PARA CAPACITACIÓN Y FORMACIÓN ESPECIALIZADA EN TEMAS DE LAS INDUSTRIAS CREATIVAS Y CULTURALES INCLUIDOS EN EL PLAN DE BIENESTAR E INCENTIVOS
5th rowLUZ MARINA GONZALEZ MENDEZ
ValueCountFrequency (%)
de 837532
 
14.3%
la 287225
 
4.9%
servicios 228704
 
3.9%
y 197054
 
3.4%
en 138069
 
2.4%
para 133381
 
2.3%
a 126744
 
2.2%
el 114709
 
2.0%
del 106546
 
1.8%
profesionales 100247
 
1.7%
Other values (118291) 3604029
61.4%
2024-01-11T20:40:53.383226image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5458852
 
13.6%
E 3018841
 
7.5%
A 2900268
 
7.2%
I 2368047
 
5.9%
O 2196033
 
5.5%
S 1958919
 
4.9%
R 1867238
 
4.6%
N 1625284
 
4.0%
C 1501706
 
3.7%
D 1320606
 
3.3%
Other values (95) 16058777
39.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 25365818
63.0%
Lowercase Letter 8973955
 
22.3%
Space Separator 5458852
 
13.6%
Decimal Number 475946
 
1.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 3018841
11.9%
A 2900268
11.4%
I 2368047
9.3%
O 2196033
8.7%
S 1958919
 
7.7%
R 1867238
 
7.4%
N 1625284
 
6.4%
C 1501706
 
5.9%
D 1320606
 
5.2%
T 1258525
 
5.0%
Other values (40) 5350351
21.1%
Lowercase Letter
ValueCountFrequency (%)
e 1112848
12.4%
a 1042946
11.6%
i 834120
9.3%
o 729489
8.1%
r 682723
 
7.6%
s 659858
 
7.4%
n 642183
 
7.2%
c 521940
 
5.8%
t 468229
 
5.2%
d 458378
 
5.1%
Other values (34) 1821241
20.3%
Decimal Number
ValueCountFrequency (%)
2 136952
28.8%
0 113991
24.0%
1 64790
13.6%
3 37774
 
7.9%
4 24085
 
5.1%
5 22971
 
4.8%
9 20084
 
4.2%
7 19058
 
4.0%
8 18375
 
3.9%
6 17866
 
3.8%
Space Separator
ValueCountFrequency (%)
5458852
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34339773
85.3%
Common 5934798
 
14.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 3018841
 
8.8%
A 2900268
 
8.4%
I 2368047
 
6.9%
O 2196033
 
6.4%
S 1958919
 
5.7%
R 1867238
 
5.4%
N 1625284
 
4.7%
C 1501706
 
4.4%
D 1320606
 
3.8%
T 1258525
 
3.7%
Other values (84) 14324306
41.7%
Common
ValueCountFrequency (%)
5458852
92.0%
2 136952
 
2.3%
0 113991
 
1.9%
1 64790
 
1.1%
3 37774
 
0.6%
4 24085
 
0.4%
5 22971
 
0.4%
9 20084
 
0.3%
7 19058
 
0.3%
8 18375
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39690536
98.5%
None 584035
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5458852
 
13.8%
E 3018841
 
7.6%
A 2900268
 
7.3%
I 2368047
 
6.0%
O 2196033
 
5.5%
S 1958919
 
4.9%
R 1867238
 
4.7%
N 1625284
 
4.1%
C 1501706
 
3.8%
D 1320606
 
3.3%
Other values (53) 15474742
39.0%
None
ValueCountFrequency (%)
Ó 214201
36.7%
ó 158878
27.2%
Í 48222
 
8.3%
í 37311
 
6.4%
Á 23188
 
4.0%
é 22207
 
3.8%
É 22006
 
3.8%
Ñ 21808
 
3.7%
á 13114
 
2.2%
Ú 8591
 
1.5%
Other values (32) 14509
 
2.5%
Distinct378276
Distinct (%)77.4%
Missing11332
Missing (%)2.3%
Memory size7.6 MiB
2024-01-11T20:40:53.656993image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length500
Median length360
Mean length228.1354642
Min length8

Characters and Unicode

Total characters111482501
Distinct characters108
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique339462 ?
Unique (%)69.5%

Sample

1st rowPrestar con sus propios medios con plena autonomía técnica y administrativa los servicios profesionales a la Subdirección de Sistemas de Información de Tierras de la Dirección de Gestión del Ordenamiento Social de la propiedad para apoyar las actividades relacionadas con la implementación consolidación y seguimiento de la cadena de procesos del registro de sujetos de ordenamiento RESO al igual que su correcta gestión en el Sistema Integrado de Tierras
2nd rowPrestar servicios personales de apoyo a la gestión en la Gerencia SeccionalValle del Cauca apoyando las actividades relacionadas con la expedición de Guías Sanitarias de MovilizaciónInterna
3rd rowCONVSDDE202021LOGTHTU Prestación de servicios para coordinar los procesos preoperativos operativos de entrenamiento levantamiento de la información acompañamiento a fuentes captura y validación de la información de la EMSB así como el cumplimento de los indicadores de cobertura oportunidad y calidad de la información correspondiente a los periodos a recolectar en la ejecución del contrato
4th rowSERVICIOS PARA CAPACITACIÓN Y FORMACIÓN ESPECIALIZADA EN TEMAS DE LAS INDUSTRIAS CREATIVAS Y CULTURALES INCLUIDOS EN EL PLAN DE BIENESTAR E INCENTIVOS PARA LOS FUNCIONARIOS PÚBLICOS Y TRABAJADORES OFICIALES DE LA EMPRESA DE VIVIENDA Y DESARROLLO URBANO Y RURAL DEL MUNICIPIO DE ENVIGADO
5th rowPrestar los servicios profesionales en salud como auditor para consolidar la información realizar las validaciones asistenciales en atención de usuarios red externa red interna cruce de cuentas de integración funcional en los establecimientos de Sanidad Militar entre las Fuerzas en el Grupo de Prestación y Operación de Servicios de Salud en la Dirección General de Sanidad Militar
ValueCountFrequency (%)
de 2172640
 
13.1%
la 932884
 
5.6%
y 669947
 
4.0%
en 537624
 
3.2%
el 462527
 
2.8%
del 430275
 
2.6%
para 395477
 
2.4%
servicios 357169
 
2.1%
a 335056
 
2.0%
los 296768
 
1.8%
Other values (151426) 10057241
60.4%
2024-01-11T20:40:54.114301image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16350620
 
14.7%
E 6728462
 
6.0%
A 6528018
 
5.9%
I 4995481
 
4.5%
e 4782568
 
4.3%
a 4565785
 
4.1%
O 4398253
 
3.9%
S 3947550
 
3.5%
R 3790972
 
3.4%
N 3627788
 
3.3%
Other values (98) 51767004
46.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 55305161
49.6%
Lowercase Letter 38910512
34.9%
Space Separator 16350620
 
14.7%
Decimal Number 916208
 
0.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 6728462
12.2%
A 6528018
11.8%
I 4995481
9.0%
O 4398253
 
8.0%
S 3947550
 
7.1%
R 3790972
 
6.9%
N 3627788
 
6.6%
C 3281099
 
5.9%
D 3213556
 
5.8%
L 3005096
 
5.4%
Other values (40) 11788886
21.3%
Lowercase Letter
ValueCountFrequency (%)
e 4782568
12.3%
a 4565785
11.7%
i 3475671
8.9%
o 3202975
8.2%
r 2786504
 
7.2%
s 2753370
 
7.1%
n 2739054
 
7.0%
c 2246423
 
5.8%
l 2200056
 
5.7%
d 2165617
 
5.6%
Other values (37) 7992489
20.5%
Decimal Number
ValueCountFrequency (%)
2 238748
26.1%
0 228022
24.9%
1 131591
14.4%
3 68908
 
7.5%
4 49289
 
5.4%
6 44763
 
4.9%
5 42378
 
4.6%
9 39330
 
4.3%
7 38460
 
4.2%
8 34719
 
3.8%
Space Separator
ValueCountFrequency (%)
16350620
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 94215673
84.5%
Common 17266828
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 6728462
 
7.1%
A 6528018
 
6.9%
I 4995481
 
5.3%
e 4782568
 
5.1%
a 4565785
 
4.8%
O 4398253
 
4.7%
S 3947550
 
4.2%
R 3790972
 
4.0%
N 3627788
 
3.9%
i 3475671
 
3.7%
Other values (87) 47375125
50.3%
Common
ValueCountFrequency (%)
16350620
94.7%
2 238748
 
1.4%
0 228022
 
1.3%
1 131591
 
0.8%
3 68908
 
0.4%
4 49289
 
0.3%
6 44763
 
0.3%
5 42378
 
0.2%
9 39330
 
0.2%
7 38460
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 109765609
98.5%
None 1716892
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16350620
 
14.9%
E 6728462
 
6.1%
A 6528018
 
5.9%
I 4995481
 
4.6%
e 4782568
 
4.4%
a 4565785
 
4.2%
O 4398253
 
4.0%
S 3947550
 
3.6%
R 3790972
 
3.5%
N 3627788
 
3.3%
Other values (53) 50050112
45.6%
None
ValueCountFrequency (%)
ó 533018
31.0%
Ó 481446
28.0%
í 159196
 
9.3%
Í 129917
 
7.6%
é 75907
 
4.4%
á 71166
 
4.1%
Á 66955
 
3.9%
É 63334
 
3.7%
Ñ 43021
 
2.5%
ú 31605
 
1.8%
Other values (35) 61327
 
3.6%

Fase
Text

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:54.230575image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length43
Median length22
Mean length22.270326
Min length11

Characters and Unicode

Total characters11135163
Distinct characters34
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPresentación de oferta
2nd rowPresentación de oferta
3rd rowPresentación de oferta
4th rowPresentación de oferta
5th rowPresentación de oferta
ValueCountFrequency (%)
de 500009
33.1%
presentación 490397
32.5%
oferta 478757
31.7%
observaciones 10884
 
0.7%
ofertas 5163
 
0.3%
fase 5093
 
0.3%
manifestación 4388
 
0.3%
interés 4388
 
0.3%
menor 4388
 
0.3%
cuantía 4388
 
0.3%
Other values (11) 2477
 
0.2%
2024-01-11T20:40:54.393343image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2007224
18.0%
n 1015227
9.1%
1010332
9.1%
a 1008467
9.1%
r 994360
8.9%
t 987885
8.9%
s 531878
 
4.8%
i 517226
 
4.6%
o 511607
 
4.6%
c 507590
 
4.6%
Other values (24) 2043367
18.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9603434
86.2%
Space Separator 1010332
 
9.1%
Uppercase Letter 510978
 
4.6%
Close Punctuation 5179
 
< 0.1%
Open Punctuation 5179
 
< 0.1%
Dash Punctuation 61
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2007224
20.9%
n 1015227
10.6%
a 1008467
10.5%
r 994360
10.4%
t 987885
10.3%
s 531878
 
5.5%
i 517226
 
5.4%
o 511607
 
5.3%
c 507590
 
5.3%
d 500620
 
5.2%
Other values (11) 1021350
10.6%
Uppercase Letter
ValueCountFrequency (%)
P 490604
96.0%
M 8776
 
1.7%
F 5093
 
1.0%
C 4570
 
0.9%
S 791
 
0.2%
N 515
 
0.1%
D 515
 
0.1%
E 111
 
< 0.1%
O 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1010332
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5179
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10114412
90.8%
Common 1020751
 
9.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2007224
19.8%
n 1015227
10.0%
a 1008467
10.0%
r 994360
9.8%
t 987885
9.8%
s 531878
 
5.3%
i 517226
 
5.1%
o 511607
 
5.1%
c 507590
 
5.0%
d 500620
 
4.9%
Other values (20) 1532328
15.1%
Common
ValueCountFrequency (%)
1010332
99.0%
) 5179
 
0.5%
( 5179
 
0.5%
- 61
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10630689
95.5%
None 504474
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2007224
18.9%
n 1015227
9.5%
1010332
9.5%
a 1008467
9.5%
r 994360
9.4%
t 987885
9.3%
s 531878
 
5.0%
i 517226
 
4.9%
o 511607
 
4.8%
c 507590
 
4.8%
Other values (21) 1538893
14.5%
None
ValueCountFrequency (%)
ó 495637
98.2%
é 4449
 
0.9%
í 4388
 
0.9%
Distinct2655
Distinct (%)0.5%
Missing481
Missing (%)0.1%
Memory size7.6 MiB
2024-01-11T20:40:54.567492image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters4995190
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique141 ?
Unique (%)< 0.1%

Sample

1st row01/04/2018
2nd row12/24/2021
3rd row01/28/2021
4th row05/26/2023
5th row01/16/2023
ValueCountFrequency (%)
01/28/2022 3791
 
0.8%
01/27/2022 3468
 
0.7%
01/26/2022 3384
 
0.7%
01/22/2022 2765
 
0.6%
01/25/2022 2305
 
0.5%
01/18/2022 2055
 
0.4%
01/20/2022 1917
 
0.4%
01/21/2022 1908
 
0.4%
01/14/2022 1871
 
0.4%
01/19/2022 1807
 
0.4%
Other values (2645) 474248
94.9%
2024-01-11T20:40:54.800086image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1378979
27.6%
0 1176674
23.6%
/ 999038
20.0%
1 588154
11.8%
3 288267
 
5.8%
8 119621
 
2.4%
9 109137
 
2.2%
7 93789
 
1.9%
6 88751
 
1.8%
5 78122
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3996152
80.0%
Other Punctuation 999038
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1378979
34.5%
0 1176674
29.4%
1 588154
14.7%
3 288267
 
7.2%
8 119621
 
3.0%
9 109137
 
2.7%
7 93789
 
2.3%
6 88751
 
2.2%
5 78122
 
2.0%
4 74658
 
1.9%
Other Punctuation
ValueCountFrequency (%)
/ 999038
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4995190
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1378979
27.6%
0 1176674
23.6%
/ 999038
20.0%
1 588154
11.8%
3 288267
 
5.8%
8 119621
 
2.4%
9 109137
 
2.2%
7 93789
 
1.9%
6 88751
 
1.8%
5 78122
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4995190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1378979
27.6%
0 1176674
23.6%
/ 999038
20.0%
1 588154
11.8%
3 288267
 
5.8%
8 119621
 
2.4%
9 109137
 
2.2%
7 93789
 
1.9%
6 88751
 
1.8%
5 78122
 
1.6%
Distinct2622
Distinct (%)0.5%
Missing481
Missing (%)0.1%
Memory size7.6 MiB
2024-01-11T20:40:54.984009image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters4995190
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique151 ?
Unique (%)< 0.1%

Sample

1st row01/04/2018
2nd row12/23/2021
3rd row01/27/2021
4th row05/26/2023
5th row01/16/2023
ValueCountFrequency (%)
01/28/2022 3733
 
0.7%
01/26/2022 3572
 
0.7%
01/27/2022 3147
 
0.6%
01/24/2022 2322
 
0.5%
01/22/2022 2274
 
0.5%
01/25/2022 2174
 
0.4%
01/20/2022 2145
 
0.4%
01/18/2022 2079
 
0.4%
01/21/2022 2071
 
0.4%
06/28/2023 2031
 
0.4%
Other values (2612) 473971
94.9%
2024-01-11T20:40:55.227271image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1378050
27.6%
0 1176389
23.6%
/ 999038
20.0%
1 589343
11.8%
3 288736
 
5.8%
8 120004
 
2.4%
9 107888
 
2.2%
7 93357
 
1.9%
6 88946
 
1.8%
5 78208
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3996152
80.0%
Other Punctuation 999038
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1378050
34.5%
0 1176389
29.4%
1 589343
14.7%
3 288736
 
7.2%
8 120004
 
3.0%
9 107888
 
2.7%
7 93357
 
2.3%
6 88946
 
2.2%
5 78208
 
2.0%
4 75231
 
1.9%
Other Punctuation
ValueCountFrequency (%)
/ 999038
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4995190
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1378050
27.6%
0 1176389
23.6%
/ 999038
20.0%
1 589343
11.8%
3 288736
 
5.8%
8 120004
 
2.4%
9 107888
 
2.2%
7 93357
 
1.9%
6 88946
 
1.8%
5 78208
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4995190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1378050
27.6%
0 1176389
23.6%
/ 999038
20.0%
1 589343
11.8%
3 288736
 
5.8%
8 120004
 
2.4%
9 107888
 
2.2%
7 93357
 
1.9%
6 88946
 
1.8%
5 78208
 
1.6%

Fecha de Publicacion (Fase Planeacion Precalificacion)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing500000
Missing (%)100.0%
Memory size7.6 MiB

Fecha de Publicacion (Fase Seleccion Precalificacion)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing500000
Missing (%)100.0%
Memory size7.6 MiB
Distinct1346
Distinct (%)30.3%
Missing495551
Missing (%)99.1%
Memory size7.6 MiB
2024-01-11T20:40:55.406549image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters44490
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique362 ?
Unique (%)8.1%

Sample

1st row05/10/2023
2nd row05/10/2022
3rd row09/03/2019
4th row09/20/2023
5th row04/03/2018
ValueCountFrequency (%)
09/06/2023 16
 
0.4%
08/15/2023 16
 
0.4%
08/10/2023 16
 
0.4%
06/14/2023 14
 
0.3%
10/04/2023 14
 
0.3%
10/24/2023 13
 
0.3%
06/14/2022 12
 
0.3%
10/11/2021 12
 
0.3%
10/12/2021 12
 
0.3%
11/29/2022 11
 
0.2%
Other values (1336) 4313
96.9%
2024-01-11T20:40:55.645093image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11080
24.9%
0 10505
23.6%
/ 8898
20.0%
1 5503
12.4%
3 2073
 
4.7%
9 1477
 
3.3%
8 1344
 
3.0%
7 985
 
2.2%
6 929
 
2.1%
5 869
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35592
80.0%
Other Punctuation 8898
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11080
31.1%
0 10505
29.5%
1 5503
15.5%
3 2073
 
5.8%
9 1477
 
4.1%
8 1344
 
3.8%
7 985
 
2.8%
6 929
 
2.6%
5 869
 
2.4%
4 827
 
2.3%
Other Punctuation
ValueCountFrequency (%)
/ 8898
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11080
24.9%
0 10505
23.6%
/ 8898
20.0%
1 5503
12.4%
3 2073
 
4.7%
9 1477
 
3.3%
8 1344
 
3.0%
7 985
 
2.2%
6 929
 
2.1%
5 869
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11080
24.9%
0 10505
23.6%
/ 8898
20.0%
1 5503
12.4%
3 2073
 
4.7%
9 1477
 
3.3%
8 1344
 
3.0%
7 985
 
2.2%
6 929
 
2.1%
5 869
 
2.0%
Distinct1703
Distinct (%)15.4%
Missing488960
Missing (%)97.8%
Memory size7.6 MiB
2024-01-11T20:40:55.822602image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters110400
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique312 ?
Unique (%)2.8%

Sample

1st row11/23/2018
2nd row11/05/2021
3rd row08/18/2022
4th row08/26/2019
5th row01/26/2022
ValueCountFrequency (%)
10/29/2021 26
 
0.2%
06/30/2022 25
 
0.2%
11/18/2021 25
 
0.2%
08/31/2022 24
 
0.2%
04/29/2022 23
 
0.2%
05/23/2023 23
 
0.2%
10/04/2023 22
 
0.2%
08/17/2023 22
 
0.2%
10/12/2023 22
 
0.2%
10/25/2022 22
 
0.2%
Other values (1693) 10806
97.9%
2024-01-11T20:40:56.052779image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 27908
25.3%
0 26068
23.6%
/ 22080
20.0%
1 13523
12.2%
3 5268
 
4.8%
9 3626
 
3.3%
8 3427
 
3.1%
7 2260
 
2.0%
5 2156
 
2.0%
6 2125
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88320
80.0%
Other Punctuation 22080
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 27908
31.6%
0 26068
29.5%
1 13523
15.3%
3 5268
 
6.0%
9 3626
 
4.1%
8 3427
 
3.9%
7 2260
 
2.6%
5 2156
 
2.4%
6 2125
 
2.4%
4 1959
 
2.2%
Other Punctuation
ValueCountFrequency (%)
/ 22080
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 110400
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 27908
25.3%
0 26068
23.6%
/ 22080
20.0%
1 13523
12.2%
3 5268
 
4.8%
9 3626
 
3.3%
8 3427
 
3.1%
7 2260
 
2.0%
5 2156
 
2.0%
6 2125
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 110400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 27908
25.3%
0 26068
23.6%
/ 22080
20.0%
1 13523
12.2%
3 5268
 
4.8%
9 3626
 
3.3%
8 3427
 
3.1%
7 2260
 
2.0%
5 2156
 
2.0%
6 2125
 
1.9%
Distinct2601
Distinct (%)0.5%
Missing15970
Missing (%)3.2%
Memory size7.6 MiB
2024-01-11T20:40:56.229776image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters4840300
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)< 0.1%

Sample

1st row01/04/2018
2nd row12/23/2021
3rd row01/27/2021
4th row05/26/2023
5th row01/16/2023
ValueCountFrequency (%)
01/28/2022 3731
 
0.8%
01/26/2022 3566
 
0.7%
01/27/2022 3144
 
0.6%
01/24/2022 2319
 
0.5%
01/22/2022 2274
 
0.5%
01/25/2022 2172
 
0.4%
01/20/2022 2143
 
0.4%
01/18/2022 2076
 
0.4%
01/21/2022 2066
 
0.4%
06/28/2023 2014
 
0.4%
Other values (2591) 458525
94.7%
2024-01-11T20:40:56.463027image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1339062
27.7%
0 1139816
23.5%
/ 968060
20.0%
1 570317
11.8%
3 281395
 
5.8%
8 115233
 
2.4%
9 102785
 
2.1%
7 90112
 
1.9%
6 85892
 
1.8%
5 75183
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3872240
80.0%
Other Punctuation 968060
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1339062
34.6%
0 1139816
29.4%
1 570317
14.7%
3 281395
 
7.3%
8 115233
 
3.0%
9 102785
 
2.7%
7 90112
 
2.3%
6 85892
 
2.2%
5 75183
 
1.9%
4 72445
 
1.9%
Other Punctuation
ValueCountFrequency (%)
/ 968060
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4840300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1339062
27.7%
0 1139816
23.5%
/ 968060
20.0%
1 570317
11.8%
3 281395
 
5.8%
8 115233
 
2.4%
9 102785
 
2.1%
7 90112
 
1.9%
6 85892
 
1.8%
5 75183
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4840300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1339062
27.7%
0 1139816
23.5%
/ 968060
20.0%
1 570317
11.8%
3 281395
 
5.8%
8 115233
 
2.4%
9 102785
 
2.1%
7 90112
 
1.9%
6 85892
 
1.8%
5 75183
 
1.6%

Precio Base
Real number (ℝ)

SKEWED  ZEROS 

Distinct171562
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean332229671.2
Minimum-1.02325565 × 1010
Maximum7.46024 × 1012
Zeros12328
Zeros (%)2.5%
Negative12070
Negative (%)2.4%
Memory size7.6 MiB
2024-01-11T20:40:56.549208image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum-1.02325565 × 1010
5-th percentile38891.2
Q15950000
median14700000
Q336000000
95-th percentile340000000
Maximum7.46024 × 1012
Range7.470472556 × 1012
Interquartile range (IQR)30050000

Descriptive statistics

Standard deviation1.755048684 × 1010
Coefficient of variation (CV)52.82636791
Kurtosis85807.08953
Mean332229671.2
Median Absolute Deviation (MAD)11100000
Skewness254.1476829
Sum1.661148356 × 1014
Variance3.080195884 × 1020
MonotonicityNot monotonic
2024-01-11T20:40:56.622889image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12328
 
2.5%
-1 12061
 
2.4%
12000000 4003
 
0.8%
6000000 3831
 
0.8%
10000000 3505
 
0.7%
9000000 3202
 
0.6%
15000000 2940
 
0.6%
8000000 2856
 
0.6%
20000000 2812
 
0.6%
3000000 2713
 
0.5%
Other values (171552) 449749
89.9%
ValueCountFrequency (%)
-1.02325565 × 10102
< 0.1%
-799983710 2
< 0.1%
-397166484 1
< 0.1%
-31935634 1
< 0.1%
-18035793 1
< 0.1%
ValueCountFrequency (%)
7.46024 × 10121
< 0.1%
4.8315 × 10121
< 0.1%
3.430905447 × 10121
< 0.1%
3.354099 × 10121
< 0.1%
2.765993131 × 10121
< 0.1%
Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:56.762278image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length59
Median length20
Mean length24.092228
Min length14

Characters and Unicode

Total characters12046114
Distinct characters41
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowContratación directa
2nd rowContratación directa
3rd rowContratación directa
4th rowContratación régimen especial
5th rowContratación directa
ValueCountFrequency (%)
contratación 434305
33.8%
directa 281298
21.9%
régimen 153007
 
11.9%
especial 153007
 
11.9%
cuantía 39262
 
3.1%
de 27666
 
2.2%
mínima 25408
 
2.0%
abreviada 21335
 
1.7%
selección 21116
 
1.6%
menor 14073
 
1.1%
Other values (29) 114974
 
8.9%
2024-01-11T20:40:56.934070image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1529818
12.7%
t 1230879
10.2%
n 1173680
9.7%
i 1171015
9.7%
c 988513
8.2%
r 970758
8.1%
e 906298
 
7.5%
785451
 
6.5%
o 544619
 
4.5%
ó 471604
 
3.9%
Other values (31) 2273479
18.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10647272
88.4%
Space Separator 785451
 
6.5%
Uppercase Letter 577423
 
4.8%
Open Punctuation 10639
 
0.1%
Close Punctuation 10639
 
0.1%
Connector Punctuation 7345
 
0.1%
Decimal Number 4407
 
< 0.1%
Dash Punctuation 2938
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1529818
14.4%
t 1230879
11.6%
n 1173680
11.0%
i 1171015
11.0%
c 988513
9.3%
r 970758
9.1%
e 906298
8.5%
o 544619
 
5.1%
ó 471604
 
4.4%
d 348042
 
3.3%
Other values (13) 1312046
12.3%
Uppercase Letter
ValueCountFrequency (%)
C 455554
78.9%
M 41344
 
7.2%
S 36752
 
6.4%
A 14248
 
2.5%
P 14032
 
2.4%
D 6991
 
1.2%
L 5315
 
0.9%
E 1546
 
0.3%
O 1422
 
0.2%
I 219
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 1469
33.3%
0 1469
33.3%
1 1469
33.3%
Space Separator
ValueCountFrequency (%)
785451
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10639
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10639
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7345
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2938
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11224695
93.2%
Common 821419
 
6.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1529818
13.6%
t 1230879
11.0%
n 1173680
10.5%
i 1171015
10.4%
c 988513
8.8%
r 970758
8.6%
e 906298
8.1%
o 544619
 
4.9%
ó 471604
 
4.2%
C 455554
 
4.1%
Other values (23) 1781957
15.9%
Common
ValueCountFrequency (%)
785451
95.6%
( 10639
 
1.3%
) 10639
 
1.3%
_ 7345
 
0.9%
- 2938
 
0.4%
2 1469
 
0.2%
0 1469
 
0.2%
1 1469
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11351687
94.2%
None 694427
 
5.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1529818
13.5%
t 1230879
10.8%
n 1173680
10.3%
i 1171015
10.3%
c 988513
8.7%
r 970758
8.6%
e 906298
8.0%
785451
6.9%
o 544619
 
4.8%
C 455554
 
4.0%
Other values (27) 1595102
14.1%
None
ValueCountFrequency (%)
ó 471604
67.9%
é 154307
 
22.2%
í 64670
 
9.3%
ú 3846
 
0.6%
Distinct37
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:57.063623image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length90
Median length44
Mean length34.364448
Min length2

Characters and Unicode

Total characters17182224
Distinct characters58
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowServicios profesionales y apoyo a la gestión
2nd rowServicios profesionales y apoyo a la gestión
3rd rowServicios profesionales y apoyo a la gestión
4th rowRegla aplicable
5th rowServicios profesionales y apoyo a la gestión
ValueCountFrequency (%)
la 298561
11.4%
y 276388
10.5%
servicios 268845
10.2%
a 260775
9.9%
gestión 260536
9.9%
profesionales 260536
9.9%
apoyo 260536
9.9%
regla 101456
 
3.9%
aplicable 101456
 
3.9%
de 71056
 
2.7%
Other values (101) 463028
17.7%
2024-01-11T20:40:57.257658image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2123173
12.4%
e 1742353
 
10.1%
a 1604346
 
9.3%
o 1554444
 
9.0%
i 1341247
 
7.8%
s 1240964
 
7.2%
l 936988
 
5.5%
r 820631
 
4.8%
n 751087
 
4.4%
p 664875
 
3.9%
Other values (48) 4402116
25.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13927893
81.1%
Space Separator 2123173
 
12.4%
Uppercase Letter 534391
 
3.1%
Decimal Number 488384
 
2.8%
Other Punctuation 89781
 
0.5%
Open Punctuation 8590
 
< 0.1%
Close Punctuation 8590
 
< 0.1%
Connector Punctuation 1422
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1742353
12.5%
a 1604346
11.5%
o 1554444
11.2%
i 1341247
9.6%
s 1240964
8.9%
l 936988
 
6.7%
r 820631
 
5.9%
n 751087
 
5.4%
p 664875
 
4.8%
y 541971
 
3.9%
Other values (18) 2728987
19.6%
Uppercase Letter
ValueCountFrequency (%)
S 267827
50.1%
R 101485
 
19.0%
D 52093
 
9.7%
P 40369
 
7.6%
C 22392
 
4.2%
N 15290
 
2.9%
M 12617
 
2.4%
I 8590
 
1.6%
A 5330
 
1.0%
L 5047
 
0.9%
Other values (3) 3351
 
0.6%
Decimal Number
ValueCountFrequency (%)
0 158122
32.4%
2 108454
22.2%
1 101861
20.9%
7 56490
 
11.6%
9 54687
 
11.2%
5 5310
 
1.1%
3 3136
 
0.6%
4 175
 
< 0.1%
8 91
 
< 0.1%
6 58
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
/ 51524
57.4%
% 38025
42.4%
, 232
 
0.3%
Space Separator
ValueCountFrequency (%)
2123173
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8590
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8590
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1422
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14462284
84.2%
Common 2719940
 
15.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1742353
12.0%
a 1604346
11.1%
o 1554444
10.7%
i 1341247
9.3%
s 1240964
 
8.6%
l 936988
 
6.5%
r 820631
 
5.7%
n 751087
 
5.2%
p 664875
 
4.6%
y 541971
 
3.7%
Other values (31) 3263378
22.6%
Common
ValueCountFrequency (%)
2123173
78.1%
0 158122
 
5.8%
2 108454
 
4.0%
1 101861
 
3.7%
7 56490
 
2.1%
9 54687
 
2.0%
/ 51524
 
1.9%
% 38025
 
1.4%
( 8590
 
0.3%
) 8590
 
0.3%
Other values (7) 10424
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16846053
98.0%
None 336171
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2123173
12.6%
e 1742353
10.3%
a 1604346
 
9.5%
o 1554444
 
9.2%
i 1341247
 
8.0%
s 1240964
 
7.4%
l 936988
 
5.6%
r 820631
 
4.9%
n 751087
 
4.5%
p 664875
 
3.9%
Other values (43) 4065945
24.1%
None
ValueCountFrequency (%)
ó 272433
81.0%
í 48628
 
14.5%
ú 7647
 
2.3%
é 7356
 
2.2%
á 107
 
< 0.1%

Duracion
Real number (ℝ)

SKEWED  ZEROS 

Distinct965
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1149.578592
Minimum0
Maximum170220231
Zeros29835
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:57.336044image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median11
Q3105
95-th percentile317
Maximum170220231
Range170220231
Interquartile range (IQR)101

Descriptive statistics

Standard deviation309733.717
Coefficient of variation (CV)269.4323982
Kurtosis202208.4061
Mean1149.578592
Median Absolute Deviation (MAD)11
Skewness415.6958572
Sum574789296
Variance9.593497545 × 1010
MonotonicityNot monotonic
2024-01-11T20:40:57.411520image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 32027
 
6.4%
3 31786
 
6.4%
0 29835
 
6.0%
6 27435
 
5.5%
2 23178
 
4.6%
5 22409
 
4.5%
1 19130
 
3.8%
8 17762
 
3.6%
30 16810
 
3.4%
10 13519
 
2.7%
Other values (955) 266109
53.2%
ValueCountFrequency (%)
0 29835
6.0%
1 19130
3.8%
2 23178
4.6%
3 31786
6.4%
4 32027
6.4%
ValueCountFrequency (%)
170220231 1
< 0.1%
80111701 1
< 0.1%
80111600 1
< 0.1%
50000000 1
< 0.1%
30112023 1
< 0.1%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:57.611149image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.282474
Min length2

Characters and Unicode

Total characters2141237
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDias
2nd rowDias
3rd rowDias
4th rowMeses
5th rowMeses
ValueCountFrequency (%)
dias 262834
52.6%
meses 203023
40.6%
nd 30893
 
6.2%
años 3250
 
0.7%
2024-01-11T20:40:57.751284image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 672130
31.4%
e 406046
19.0%
D 293727
13.7%
i 262834
 
12.3%
a 262834
 
12.3%
M 203023
 
9.5%
N 30893
 
1.4%
A 3250
 
0.2%
ñ 3250
 
0.2%
o 3250
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1610344
75.2%
Uppercase Letter 530893
 
24.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 672130
41.7%
e 406046
25.2%
i 262834
 
16.3%
a 262834
 
16.3%
ñ 3250
 
0.2%
o 3250
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
D 293727
55.3%
M 203023
38.2%
N 30893
 
5.8%
A 3250
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 2141237
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 672130
31.4%
e 406046
19.0%
D 293727
13.7%
i 262834
 
12.3%
a 262834
 
12.3%
M 203023
 
9.5%
N 30893
 
1.4%
A 3250
 
0.2%
ñ 3250
 
0.2%
o 3250
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2137987
99.8%
None 3250
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 672130
31.4%
e 406046
19.0%
D 293727
13.7%
i 262834
 
12.3%
a 262834
 
12.3%
M 203023
 
9.5%
N 30893
 
1.4%
A 3250
 
0.2%
o 3250
 
0.2%
None
ValueCountFrequency (%)
ñ 3250
100.0%
Distinct2276
Distinct (%)3.0%
Missing423715
Missing (%)84.7%
Memory size7.6 MiB
2024-01-11T20:40:57.907135image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters762850
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique203 ?
Unique (%)0.3%

Sample

1st row12/11/2018
2nd row05/18/2023
3rd row06/22/2018
4th row05/24/2022
5th row07/08/2022
ValueCountFrequency (%)
11/12/2021 170
 
0.2%
11/18/2022 137
 
0.2%
04/08/2022 130
 
0.2%
06/23/2023 129
 
0.2%
08/25/2023 128
 
0.2%
11/25/2022 121
 
0.2%
08/18/2023 121
 
0.2%
06/21/2023 121
 
0.2%
05/12/2023 121
 
0.2%
06/28/2023 120
 
0.2%
Other values (2266) 74987
98.3%
2024-01-11T20:40:58.120790image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 193884
25.4%
0 177112
23.2%
/ 152570
20.0%
1 98899
13.0%
3 35364
 
4.6%
9 22875
 
3.0%
8 21954
 
2.9%
7 17526
 
2.3%
6 14970
 
2.0%
5 14076
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 610280
80.0%
Other Punctuation 152570
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 193884
31.8%
0 177112
29.0%
1 98899
16.2%
3 35364
 
5.8%
9 22875
 
3.7%
8 21954
 
3.6%
7 17526
 
2.9%
6 14970
 
2.5%
5 14076
 
2.3%
4 13620
 
2.2%
Other Punctuation
ValueCountFrequency (%)
/ 152570
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 762850
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 193884
25.4%
0 177112
23.2%
/ 152570
20.0%
1 98899
13.0%
3 35364
 
4.6%
9 22875
 
3.0%
8 21954
 
2.9%
7 17526
 
2.3%
6 14970
 
2.0%
5 14076
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 762850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 193884
25.4%
0 177112
23.2%
/ 152570
20.0%
1 98899
13.0%
3 35364
 
4.6%
9 22875
 
3.0%
8 21954
 
2.9%
7 17526
 
2.3%
6 14970
 
2.0%
5 14076
 
1.8%
Distinct1987
Distinct (%)3.5%
Missing442953
Missing (%)88.6%
Memory size7.6 MiB
2024-01-11T20:40:58.317673image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters570470
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique223 ?
Unique (%)0.4%

Sample

1st row12/20/2018
2nd row05/18/2023
3rd row06/22/2018
4th row05/24/2022
5th row07/08/2022
ValueCountFrequency (%)
11/18/2022 118
 
0.2%
12/10/2021 109
 
0.2%
11/24/2021 104
 
0.2%
11/26/2021 102
 
0.2%
11/03/2023 100
 
0.2%
12/02/2022 100
 
0.2%
12/09/2022 100
 
0.2%
06/16/2023 99
 
0.2%
11/25/2022 97
 
0.2%
12/15/2022 97
 
0.2%
Other values (1977) 56021
98.2%
2024-01-11T20:40:58.553007image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 145605
25.5%
0 130976
23.0%
/ 114094
20.0%
1 75252
13.2%
3 25698
 
4.5%
9 18163
 
3.2%
8 16838
 
3.0%
7 12082
 
2.1%
6 11339
 
2.0%
5 10508
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 456376
80.0%
Other Punctuation 114094
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 145605
31.9%
0 130976
28.7%
1 75252
16.5%
3 25698
 
5.6%
9 18163
 
4.0%
8 16838
 
3.7%
7 12082
 
2.6%
6 11339
 
2.5%
5 10508
 
2.3%
4 9915
 
2.2%
Other Punctuation
ValueCountFrequency (%)
/ 114094
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 570470
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 145605
25.5%
0 130976
23.0%
/ 114094
20.0%
1 75252
13.2%
3 25698
 
4.5%
9 18163
 
3.2%
8 16838
 
3.0%
7 12082
 
2.1%
6 11339
 
2.0%
5 10508
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 570470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 145605
25.5%
0 130976
23.0%
/ 114094
20.0%
1 75252
13.2%
3 25698
 
4.5%
9 18163
 
3.2%
8 16838
 
3.0%
7 12082
 
2.1%
6 11339
 
2.0%
5 10508
 
1.8%
Distinct2346
Distinct (%)3.1%
Missing424864
Missing (%)85.0%
Memory size7.6 MiB
2024-01-11T20:40:58.747254image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters751360
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique249 ?
Unique (%)0.3%

Sample

1st row12/20/2018
2nd row05/18/2023
3rd row06/22/2018
4th row05/24/2022
5th row07/08/2022
ValueCountFrequency (%)
11/18/2022 132
 
0.2%
11/12/2021 131
 
0.2%
06/28/2023 122
 
0.2%
05/12/2023 121
 
0.2%
11/03/2023 121
 
0.2%
03/17/2023 118
 
0.2%
06/16/2023 117
 
0.2%
06/17/2022 117
 
0.2%
11/25/2022 115
 
0.2%
11/24/2021 113
 
0.2%
Other values (2336) 73929
98.4%
2024-01-11T20:40:58.988715image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 191706
25.5%
0 174290
23.2%
/ 150272
20.0%
1 97410
13.0%
3 34481
 
4.6%
9 22397
 
3.0%
8 21568
 
2.9%
7 17456
 
2.3%
6 14852
 
2.0%
5 13802
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 601088
80.0%
Other Punctuation 150272
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 191706
31.9%
0 174290
29.0%
1 97410
16.2%
3 34481
 
5.7%
9 22397
 
3.7%
8 21568
 
3.6%
7 17456
 
2.9%
6 14852
 
2.5%
5 13802
 
2.3%
4 13126
 
2.2%
Other Punctuation
ValueCountFrequency (%)
/ 150272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 751360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 191706
25.5%
0 174290
23.2%
/ 150272
20.0%
1 97410
13.0%
3 34481
 
4.6%
9 22397
 
3.0%
8 21568
 
2.9%
7 17456
 
2.3%
6 14852
 
2.0%
5 13802
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 751360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 191706
25.5%
0 174290
23.2%
/ 150272
20.0%
1 97410
13.0%
3 34481
 
4.6%
9 22397
 
3.0%
8 21568
 
2.9%
7 17456
 
2.3%
6 14852
 
2.0%
5 13802
 
1.8%
Distinct965
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:59.189403image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length7.461842
Min length3

Characters and Unicode

Total characters3730921
Distinct characters58
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)< 0.1%

Sample

1st rowBogotá
2nd rowBogotá
3rd rowBogotá
4th rowEnvigado
5th rowBogotá
ValueCountFrequency (%)
bogotá 154320
27.2%
cali 30898
 
5.4%
medellín 27717
 
4.9%
no 19570
 
3.4%
definida 19570
 
3.4%
bucaramanga 12412
 
2.2%
san 9980
 
1.8%
cartagena 9469
 
1.7%
ibagué 8767
 
1.5%
villavicencio 8328
 
1.5%
Other values (955) 266947
47.0%
2024-01-11T20:40:59.456947image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 476576
12.8%
o 450898
 
12.1%
t 227078
 
6.1%
e 216744
 
5.8%
g 209055
 
5.6%
i 207958
 
5.6%
l 200514
 
5.4%
n 194095
 
5.2%
B 185679
 
5.0%
á 171341
 
4.6%
Other values (48) 1190983
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3114535
83.5%
Uppercase Letter 548408
 
14.7%
Space Separator 67978
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 476576
15.3%
o 450898
14.5%
t 227078
 
7.3%
e 216744
 
7.0%
g 209055
 
6.7%
i 207958
 
6.7%
l 200514
 
6.4%
n 194095
 
6.2%
á 171341
 
5.5%
r 151283
 
4.9%
Other values (21) 608993
19.6%
Uppercase Letter
ValueCountFrequency (%)
B 185679
33.9%
C 66232
 
12.1%
M 54334
 
9.9%
P 37160
 
6.8%
S 34752
 
6.3%
N 29674
 
5.4%
A 20516
 
3.7%
V 16748
 
3.1%
T 12432
 
2.3%
I 11681
 
2.1%
Other values (16) 79200
14.4%
Space Separator
ValueCountFrequency (%)
67978
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3662943
98.2%
Common 67978
 
1.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 476576
13.0%
o 450898
12.3%
t 227078
 
6.2%
e 216744
 
5.9%
g 209055
 
5.7%
i 207958
 
5.7%
l 200514
 
5.5%
n 194095
 
5.3%
B 185679
 
5.1%
á 171341
 
4.7%
Other values (47) 1123005
30.7%
Common
ValueCountFrequency (%)
67978
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3482486
93.3%
None 248435
 
6.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 476576
13.7%
o 450898
12.9%
t 227078
 
6.5%
e 216744
 
6.2%
g 209055
 
6.0%
i 207958
 
6.0%
l 200514
 
5.8%
n 194095
 
5.6%
B 185679
 
5.3%
r 151283
 
4.3%
Other values (39) 962606
27.6%
None
ValueCountFrequency (%)
á 171341
69.0%
í 38969
 
15.7%
é 15978
 
6.4%
ó 9786
 
3.9%
ú 8403
 
3.4%
ñ 3756
 
1.5%
ü 177
 
0.1%
Á 24
 
< 0.1%
Ú 1
 
< 0.1%
Distinct9337
Distinct (%)1.9%
Missing148
Missing (%)< 0.1%
Memory size7.6 MiB
2024-01-11T20:40:59.617419image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length70
Median length58
Mean length26.93819371
Min length2

Characters and Unicode

Total characters13465110
Distinct characters81
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2365 ?
Unique (%)0.5%

Sample

1st rowGESTIÓN CONTRACTUAL
2nd rowGRUPO GESTION CONTRACTUAL
3rd rowSERVICIOS PROFESIONALES Y DE APOYO A LA GESTIÓN
4th rowEMPRESA DE VIVIENDA Y DESARROLLO URBANO Y RURAL DESUR
5th rowDIRECCION GENERAL DE SANIDAD MILITAR
ValueCountFrequency (%)
de 267736
 
15.5%
contratacion 78853
 
4.6%
contratación 65515
 
3.8%
secretaria 58527
 
3.4%
y 53751
 
3.1%
unidad 43257
 
2.5%
oficina 35562
 
2.1%
contractual 31898
 
1.9%
grupo 28268
 
1.6%
dirección 27675
 
1.6%
Other values (6423) 1033121
59.9%
2024-01-11T20:40:59.860398image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1257929
 
9.3%
A 1207436
 
9.0%
I 957752
 
7.1%
C 898471
 
6.7%
E 887260
 
6.6%
N 786064
 
5.8%
R 783684
 
5.8%
O 752202
 
5.6%
T 703302
 
5.2%
D 573772
 
4.3%
Other values (71) 4657238
34.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 9632348
71.5%
Lowercase Letter 2524321
 
18.7%
Space Separator 1257929
 
9.3%
Decimal Number 50512
 
0.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1207436
12.5%
I 957752
9.9%
C 898471
9.3%
E 887260
9.2%
N 786064
8.2%
R 783684
8.1%
O 752202
7.8%
T 703302
7.3%
D 573772
 
6.0%
S 499356
 
5.2%
Other values (26) 1583049
16.4%
Lowercase Letter
ValueCountFrequency (%)
a 326112
12.9%
e 275799
10.9%
i 271232
10.7%
r 228018
9.0%
n 226918
9.0%
t 193993
7.7%
c 193647
7.7%
o 170596
6.8%
d 148057
 
5.9%
s 93256
 
3.7%
Other values (24) 396693
15.7%
Decimal Number
ValueCountFrequency (%)
2 18149
35.9%
0 13236
26.2%
1 7459
14.8%
3 5603
 
11.1%
4 1745
 
3.5%
5 1125
 
2.2%
7 877
 
1.7%
8 876
 
1.7%
6 814
 
1.6%
9 628
 
1.2%
Space Separator
ValueCountFrequency (%)
1257929
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12156669
90.3%
Common 1308441
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1207436
 
9.9%
I 957752
 
7.9%
C 898471
 
7.4%
E 887260
 
7.3%
N 786064
 
6.5%
R 783684
 
6.4%
O 752202
 
6.2%
T 703302
 
5.8%
D 573772
 
4.7%
S 499356
 
4.1%
Other values (60) 4107370
33.8%
Common
ValueCountFrequency (%)
1257929
96.1%
2 18149
 
1.4%
0 13236
 
1.0%
1 7459
 
0.6%
3 5603
 
0.4%
4 1745
 
0.1%
5 1125
 
0.1%
7 877
 
0.1%
8 876
 
0.1%
6 814
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13242004
98.3%
None 223106
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1257929
 
9.5%
A 1207436
 
9.1%
I 957752
 
7.2%
C 898471
 
6.8%
E 887260
 
6.7%
N 786064
 
5.9%
R 783684
 
5.9%
O 752202
 
5.7%
T 703302
 
5.3%
D 573772
 
4.3%
Other values (53) 4434132
33.5%
None
ValueCountFrequency (%)
Ó 95537
42.8%
ó 56681
25.4%
Í 24615
 
11.0%
í 23130
 
10.4%
Á 4459
 
2.0%
ú 3092
 
1.4%
Ú 3063
 
1.4%
á 2794
 
1.3%
é 2718
 
1.2%
Ñ 2499
 
1.1%
Other values (8) 4518
 
2.0%

Proveedores Invitados
Real number (ℝ)

ZEROS 

Distinct2683
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.320422
Minimum0
Maximum12478
Zeros424504
Zeros (%)84.9%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:40:59.947062image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile40
Maximum12478
Range12478
Interquartile range (IQR)0

Descriptive statistics

Standard deviation192.7336076
Coefficient of variation (CV)9.039858948
Kurtosis430.0239298
Mean21.320422
Median Absolute Deviation (MAD)0
Skewness17.96835058
Sum10660211
Variance37146.2435
MonotonicityNot monotonic
2024-01-11T20:41:00.024004image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 424504
84.9%
1 6523
 
1.3%
10 2345
 
0.5%
5 2341
 
0.5%
6 2244
 
0.4%
4 2240
 
0.4%
3 2189
 
0.4%
7 2070
 
0.4%
2 2038
 
0.4%
8 1994
 
0.4%
Other values (2673) 51512
 
10.3%
ValueCountFrequency (%)
0 424504
84.9%
1 6523
 
1.3%
2 2038
 
0.4%
3 2189
 
0.4%
4 2240
 
0.4%
ValueCountFrequency (%)
12478 1
< 0.1%
10454 1
< 0.1%
8072 1
< 0.1%
7998 1
< 0.1%
7707 1
< 0.1%

Proveedores con Invitacion Directa
Real number (ℝ)

SKEWED  ZEROS 

Distinct158
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.133978
Minimum0
Maximum341
Zeros495371
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:00.103439image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum341
Range341
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.735605027
Coefficient of variation (CV)20.41831515
Kurtosis3352.772361
Mean0.133978
Median Absolute Deviation (MAD)0
Skewness48.52504936
Sum66989
Variance7.483534863
MonotonicityNot monotonic
2024-01-11T20:41:00.175730image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 495371
99.1%
10 768
 
0.2%
2 374
 
0.1%
3 341
 
0.1%
4 325
 
0.1%
1 298
 
0.1%
5 272
 
0.1%
6 249
 
< 0.1%
7 216
 
< 0.1%
8 188
 
< 0.1%
Other values (148) 1598
 
0.3%
ValueCountFrequency (%)
0 495371
99.1%
1 298
 
0.1%
2 374
 
0.1%
3 341
 
0.1%
4 325
 
0.1%
ValueCountFrequency (%)
341 1
< 0.1%
298 1
< 0.1%
289 1
< 0.1%
273 1
< 0.1%
255 1
< 0.1%

Visualizaciones del Procedimiento
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros500000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:00.242066image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2024-01-11T20:41:00.282826image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 500000
100.0%
ValueCountFrequency (%)
0 500000
100.0%
ValueCountFrequency (%)
0 500000
100.0%

Proveedores que Manifestaron Interes
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros500000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:00.328133image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2024-01-11T20:41:00.369167image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 500000
100.0%
ValueCountFrequency (%)
0 500000
100.0%
ValueCountFrequency (%)
0 500000
100.0%

Respuestas al Procedimiento
Real number (ℝ)

SKEWED  ZEROS 

Distinct142
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.46448
Minimum0
Maximum441
Zeros445072
Zeros (%)89.0%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:00.433047image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum441
Range441
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.309502717
Coefficient of variation (CV)7.125178086
Kurtosis1383.581534
Mean0.46448
Median Absolute Deviation (MAD)0
Skewness26.65565655
Sum232240
Variance10.95280824
MonotonicityNot monotonic
2024-01-11T20:41:00.617611image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 445072
89.0%
1 23453
 
4.7%
2 9391
 
1.9%
3 6146
 
1.2%
4 3824
 
0.8%
5 2693
 
0.5%
6 1864
 
0.4%
7 1361
 
0.3%
8 974
 
0.2%
9 773
 
0.2%
Other values (132) 4449
 
0.9%
ValueCountFrequency (%)
0 445072
89.0%
1 23453
 
4.7%
2 9391
 
1.9%
3 6146
 
1.2%
4 3824
 
0.8%
ValueCountFrequency (%)
441 1
 
< 0.1%
208 1
 
< 0.1%
190 4
< 0.1%
189 4
< 0.1%
170 2
< 0.1%

Respuestas Externas
Real number (ℝ)

SKEWED  ZEROS 

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.003808
Minimum0
Maximum24
Zeros498745
Zeros (%)99.7%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:00.675120image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1125945136
Coefficient of variation (CV)29.56788697
Kurtosis11934.43928
Mean0.003808
Median Absolute Deviation (MAD)0
Skewness83.93595492
Sum1904
Variance0.01267752449
MonotonicityNot monotonic
2024-01-11T20:41:00.726158image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 498745
99.7%
1 1011
 
0.2%
2 90
 
< 0.1%
3 69
 
< 0.1%
4 52
 
< 0.1%
5 8
 
< 0.1%
7 6
 
< 0.1%
6 6
 
< 0.1%
9 4
 
< 0.1%
19 3
 
< 0.1%
Other values (5) 6
 
< 0.1%
ValueCountFrequency (%)
0 498745
99.7%
1 1011
 
0.2%
2 90
 
< 0.1%
3 69
 
< 0.1%
4 52
 
< 0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
19 3
< 0.1%
17 1
 
< 0.1%
14 1
 
< 0.1%
12 1
 
< 0.1%

Conteo de Respuestas a Ofertas
Real number (ℝ)

SKEWED  ZEROS 

Distinct46
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01435
Minimum0
Maximum148
Zeros498950
Zeros (%)99.8%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:00.801366image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum148
Range148
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7126044437
Coefficient of variation (CV)49.65884625
Kurtosis20197.98067
Mean0.01435
Median Absolute Deviation (MAD)0
Skewness123.8939561
Sum7175
Variance0.5078050931
MonotonicityNot monotonic
2024-01-11T20:41:00.871435image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 498950
99.8%
2 235
 
< 0.1%
1 204
 
< 0.1%
3 144
 
< 0.1%
4 107
 
< 0.1%
5 67
 
< 0.1%
6 50
 
< 0.1%
8 32
 
< 0.1%
9 30
 
< 0.1%
7 28
 
< 0.1%
Other values (36) 153
 
< 0.1%
ValueCountFrequency (%)
0 498950
99.8%
1 204
 
< 0.1%
2 235
 
< 0.1%
3 144
 
< 0.1%
4 107
 
< 0.1%
ValueCountFrequency (%)
148 3
< 0.1%
126 2
< 0.1%
107 3
< 0.1%
81 1
 
< 0.1%
67 1
 
< 0.1%

Proveedores Unicos con Respuestas
Real number (ℝ)

SKEWED  ZEROS 

Distinct141
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.446286
Minimum0
Maximum441
Zeros445958
Zeros (%)89.2%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:00.951044image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum441
Range441
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.169496947
Coefficient of variation (CV)7.101941237
Kurtosis1553.32404
Mean0.446286
Median Absolute Deviation (MAD)0
Skewness27.83566374
Sum223143
Variance10.0457109
MonotonicityNot monotonic
2024-01-11T20:41:01.022020image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 445958
89.2%
1 22831
 
4.6%
2 9402
 
1.9%
3 6138
 
1.2%
4 3861
 
0.8%
5 2684
 
0.5%
6 1829
 
0.4%
7 1359
 
0.3%
8 979
 
0.2%
9 769
 
0.2%
Other values (131) 4190
 
0.8%
ValueCountFrequency (%)
0 445958
89.2%
1 22831
 
4.6%
2 9402
 
1.9%
3 6138
 
1.2%
4 3861
 
0.8%
ValueCountFrequency (%)
441 1
 
< 0.1%
208 1
 
< 0.1%
190 4
< 0.1%
189 4
< 0.1%
170 2
< 0.1%

Numero de Lotes
Real number (ℝ)

SKEWED  ZEROS 

Distinct109
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.147904
Minimum0
Maximum562
Zeros489486
Zeros (%)97.9%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:01.103907image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum562
Range562
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.467404422
Coefficient of variation (CV)16.68247256
Kurtosis7110.275449
Mean0.147904
Median Absolute Deviation (MAD)0
Skewness57.74482832
Sum73952
Variance6.088084583
MonotonicityNot monotonic
2024-01-11T20:41:01.177738image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 489486
97.9%
2 3176
 
0.6%
3 1560
 
0.3%
1 1237
 
0.2%
4 1034
 
0.2%
5 642
 
0.1%
6 422
 
0.1%
7 329
 
0.1%
8 272
 
0.1%
10 266
 
0.1%
Other values (99) 1576
 
0.3%
ValueCountFrequency (%)
0 489486
97.9%
1 1237
 
0.2%
2 3176
 
0.6%
3 1560
 
0.3%
4 1034
 
0.2%
ValueCountFrequency (%)
562 1
< 0.1%
233 1
< 0.1%
197 2
< 0.1%
188 1
< 0.1%
181 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:01.266172image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length10.262608
Min length10

Characters and Unicode

Total characters5131304
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAdjudicado
2nd rowAdjudicado
3rd rowAdjudicado
4th rowAdjudicado
5th rowAdjudicado
ValueCountFrequency (%)
adjudicado 368696
58.4%
no 131304
 
20.8%
definido 131304
 
20.8%
2024-01-11T20:41:01.403925image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 1237392
24.1%
i 631304
12.3%
o 631304
12.3%
A 368696
 
7.2%
j 368696
 
7.2%
u 368696
 
7.2%
c 368696
 
7.2%
a 368696
 
7.2%
N 131304
 
2.6%
131304
 
2.6%
Other values (4) 525216
10.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4368696
85.1%
Uppercase Letter 631304
 
12.3%
Space Separator 131304
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 1237392
28.3%
i 631304
14.5%
o 631304
14.5%
j 368696
 
8.4%
u 368696
 
8.4%
c 368696
 
8.4%
a 368696
 
8.4%
e 131304
 
3.0%
f 131304
 
3.0%
n 131304
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
A 368696
58.4%
N 131304
 
20.8%
D 131304
 
20.8%
Space Separator
ValueCountFrequency (%)
131304
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5000000
97.4%
Common 131304
 
2.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 1237392
24.7%
i 631304
12.6%
o 631304
12.6%
A 368696
 
7.4%
j 368696
 
7.4%
u 368696
 
7.4%
c 368696
 
7.4%
a 368696
 
7.4%
N 131304
 
2.6%
D 131304
 
2.6%
Other values (3) 393912
 
7.9%
Common
ValueCountFrequency (%)
131304
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5131304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 1237392
24.1%
i 631304
12.3%
o 631304
12.3%
A 368696
 
7.2%
j 368696
 
7.2%
u 368696
 
7.2%
c 368696
 
7.2%
a 368696
 
7.2%
N 131304
 
2.6%
131304
 
2.6%
Other values (4) 525216
10.2%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.85943
Minimum50
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:01.466173image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile50
Q170
median70
Q370
95-th percentile70
Maximum200
Range150
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.83893468
Coefficient of variation (CV)0.162115272
Kurtosis2.596213178
Mean66.85943
Median Absolute Deviation (MAD)0
Skewness0.4680596356
Sum33429715
Variance117.482505
MonotonicityNot monotonic
2024-01-11T20:41:01.519235image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
70 368704
73.7%
50 110365
 
22.1%
100 19541
 
3.9%
105 1125
 
0.2%
110 256
 
0.1%
200 9
 
< 0.1%
ValueCountFrequency (%)
50 110365
 
22.1%
70 368704
73.7%
100 19541
 
3.9%
105 1125
 
0.2%
110 256
 
0.1%
ValueCountFrequency (%)
200 9
 
< 0.1%
110 256
 
0.1%
105 1125
 
0.2%
100 19541
 
3.9%
70 368704
73.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:01.564950image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1000000
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 454049
90.8%
si 45951
 
9.2%
2024-01-11T20:41:01.666915image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 454049
45.4%
o 454049
45.4%
S 45951
 
4.6%
i 45951
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 500000
50.0%
Lowercase Letter 500000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 454049
90.8%
S 45951
 
9.2%
Lowercase Letter
ValueCountFrequency (%)
o 454049
90.8%
i 45951
 
9.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 1000000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 454049
45.4%
o 454049
45.4%
S 45951
 
4.6%
i 45951
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 454049
45.4%
o 454049
45.4%
S 45951
 
4.6%
i 45951
 
4.6%
Distinct45189
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:01.831009image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length13.141834
Min length11

Characters and Unicode

Total characters6570917
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44671 ?
Unique (%)8.9%

Sample

1st rowNo Adjudicado
2nd rowNo Adjudicado
3rd rowNo Adjudicado
4th rowNo Adjudicado
5th rowNo Adjudicado
ValueCountFrequency (%)
no 454049
47.6%
adjudicado 454049
47.6%
co1.awd.1257717 18
 
< 0.1%
co1.awd.1163150 11
 
< 0.1%
co1.awd.1490918 11
 
< 0.1%
co1.awd.1440523 9
 
< 0.1%
co1.awd.596941 9
 
< 0.1%
co1.awd.7501 7
 
< 0.1%
co1.awd.63704 7
 
< 0.1%
co1.awd.486239 7
 
< 0.1%
Other values (45180) 45872
 
4.8%
2024-01-11T20:41:02.065526image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 1362147
20.7%
o 908098
13.8%
A 500000
 
7.6%
N 454049
 
6.9%
454049
 
6.9%
j 454049
 
6.9%
u 454049
 
6.9%
i 454049
 
6.9%
c 454049
 
6.9%
a 454049
 
6.9%
Other values (15) 622329
9.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4540490
69.1%
Uppercase Letter 1137853
 
17.3%
Space Separator 454049
 
6.9%
Decimal Number 346623
 
5.3%
Other Punctuation 91902
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 105001
30.3%
0 32544
 
9.4%
2 30550
 
8.8%
3 29957
 
8.6%
4 28321
 
8.2%
5 27084
 
7.8%
6 26017
 
7.5%
7 24385
 
7.0%
8 21724
 
6.3%
9 21040
 
6.1%
Lowercase Letter
ValueCountFrequency (%)
d 1362147
30.0%
o 908098
20.0%
j 454049
 
10.0%
u 454049
 
10.0%
i 454049
 
10.0%
c 454049
 
10.0%
a 454049
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
A 500000
43.9%
N 454049
39.9%
O 45951
 
4.0%
C 45951
 
4.0%
W 45951
 
4.0%
D 45951
 
4.0%
Space Separator
ValueCountFrequency (%)
454049
100.0%
Other Punctuation
ValueCountFrequency (%)
. 91902
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5678343
86.4%
Common 892574
 
13.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 1362147
24.0%
o 908098
16.0%
A 500000
 
8.8%
N 454049
 
8.0%
j 454049
 
8.0%
u 454049
 
8.0%
i 454049
 
8.0%
c 454049
 
8.0%
a 454049
 
8.0%
O 45951
 
0.8%
Other values (3) 137853
 
2.4%
Common
ValueCountFrequency (%)
454049
50.9%
1 105001
 
11.8%
. 91902
 
10.3%
0 32544
 
3.6%
2 30550
 
3.4%
3 29957
 
3.4%
4 28321
 
3.2%
5 27084
 
3.0%
6 26017
 
2.9%
7 24385
 
2.7%
Other values (2) 42764
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6570917
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 1362147
20.7%
o 908098
13.8%
A 500000
 
7.6%
N 454049
 
6.9%
454049
 
6.9%
j 454049
 
6.9%
u 454049
 
6.9%
i 454049
 
6.9%
c 454049
 
6.9%
a 454049
 
6.9%
Other values (15) 622329
9.5%
Distinct21164
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:02.258269image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.6325
Min length9

Characters and Unicode

Total characters6316250
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14327 ?
Unique (%)2.9%

Sample

1st rowNo Adjudicado
2nd rowNo Adjudicado
3rd rowNo Adjudicado
4th rowNo Adjudicado
5th rowNo Adjudicado
ValueCountFrequency (%)
no 454076
47.6%
adjudicado 454049
47.6%
700306053 235
 
< 0.1%
700326028 177
 
< 0.1%
700255011 125
 
< 0.1%
700636053 75
 
< 0.1%
700359052 75
 
< 0.1%
700827017 74
 
< 0.1%
703589531 71
 
< 0.1%
711188326 65
 
< 0.1%
Other values (21155) 45054
 
4.7%
2024-01-11T20:41:02.515546image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 1362201
21.6%
o 908152
14.4%
i 454103
 
7.2%
N 454076
 
7.2%
454076
 
7.2%
A 454049
 
7.2%
j 454049
 
7.2%
u 454049
 
7.2%
c 454049
 
7.2%
a 454049
 
7.2%
Other values (13) 413397
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4540733
71.9%
Uppercase Letter 908125
 
14.4%
Space Separator 454076
 
7.2%
Decimal Number 413316
 
6.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 1362201
30.0%
o 908152
20.0%
i 454103
 
10.0%
j 454049
 
10.0%
u 454049
 
10.0%
c 454049
 
10.0%
a 454049
 
10.0%
e 27
 
< 0.1%
f 27
 
< 0.1%
n 27
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 83292
20.2%
7 72767
17.6%
1 48252
11.7%
2 38798
9.4%
3 33294
 
8.1%
4 30827
 
7.5%
6 27356
 
6.6%
5 27241
 
6.6%
8 26297
 
6.4%
9 25192
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
N 454076
50.0%
A 454049
50.0%
Space Separator
ValueCountFrequency (%)
454076
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5448858
86.3%
Common 867392
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 1362201
25.0%
o 908152
16.7%
i 454103
 
8.3%
N 454076
 
8.3%
A 454049
 
8.3%
j 454049
 
8.3%
u 454049
 
8.3%
c 454049
 
8.3%
a 454049
 
8.3%
e 27
 
< 0.1%
Other values (2) 54
 
< 0.1%
Common
ValueCountFrequency (%)
454076
52.3%
0 83292
 
9.6%
7 72767
 
8.4%
1 48252
 
5.6%
2 38798
 
4.5%
3 33294
 
3.8%
4 30827
 
3.6%
6 27356
 
3.2%
5 27241
 
3.1%
8 26297
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6316250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 1362201
21.6%
o 908152
14.4%
i 454103
 
7.2%
N 454076
 
7.2%
454076
 
7.2%
A 454049
 
7.2%
j 454049
 
7.2%
u 454049
 
7.2%
c 454049
 
7.2%
a 454049
 
7.2%
Other values (13) 413397
 
6.5%
Distinct34
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:02.648057image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length40
Median length9
Mean length9.419568
Min length4

Characters and Unicode

Total characters4709784
Distinct characters44
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo aplica
2nd rowNo aplica
3rd rowNo aplica
4th rowNo aplica
5th rowNo aplica
ValueCountFrequency (%)
no 459377
45.7%
aplica 459377
45.7%
de 13235
 
1.3%
distrito 12360
 
1.2%
capital 12360
 
1.2%
bogotá 12360
 
1.2%
antioquia 4340
 
0.4%
cauca 3999
 
0.4%
valle 3337
 
0.3%
del 3337
 
0.3%
Other values (35) 22037
 
2.2%
2024-01-11T20:41:02.975415image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 990279
21.0%
i 513527
10.9%
o 509155
10.8%
506119
10.7%
l 488048
10.4%
p 471754
10.0%
c 469904
10.0%
N 460949
9.8%
t 61488
 
1.3%
e 27301
 
0.6%
Other values (34) 211260
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3673495
78.0%
Uppercase Letter 529999
 
11.3%
Space Separator 506119
 
10.7%
Other Punctuation 171
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 990279
27.0%
i 513527
14.0%
o 509155
13.9%
l 488048
13.3%
p 471754
12.8%
c 469904
12.8%
t 61488
 
1.7%
e 27301
 
0.7%
d 25137
 
0.7%
r 24088
 
0.7%
Other values (17) 92814
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
N 460949
87.0%
C 21878
 
4.1%
B 14904
 
2.8%
D 12360
 
2.3%
A 6265
 
1.2%
S 3715
 
0.7%
V 3490
 
0.7%
M 1428
 
0.3%
T 1147
 
0.2%
H 949
 
0.2%
Other values (5) 2914
 
0.5%
Space Separator
ValueCountFrequency (%)
506119
100.0%
Other Punctuation
ValueCountFrequency (%)
, 171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4203494
89.3%
Common 506290
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 990279
23.6%
i 513527
12.2%
o 509155
12.1%
l 488048
11.6%
p 471754
11.2%
c 469904
11.2%
N 460949
11.0%
t 61488
 
1.5%
e 27301
 
0.6%
d 25137
 
0.6%
Other values (32) 185952
 
4.4%
Common
ValueCountFrequency (%)
506119
> 99.9%
, 171
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4691141
99.6%
None 18643
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 990279
21.1%
i 513527
10.9%
o 509155
10.9%
506119
10.8%
l 488048
10.4%
p 471754
10.1%
c 469904
10.0%
N 460949
9.8%
t 61488
 
1.3%
e 27301
 
0.6%
Other values (29) 192617
 
4.1%
None
ValueCountFrequency (%)
á 15250
81.8%
í 1794
 
9.6%
ó 714
 
3.8%
ñ 697
 
3.7%
é 188
 
1.0%
Distinct497
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:03.158073image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length27
Median length9
Mean length8.88591
Min length4

Characters and Unicode

Total characters4442955
Distinct characters55
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique117 ?
Unique (%)< 0.1%

Sample

1st rowNo aplica
2nd rowNo aplica
3rd rowNo aplica
4th rowNo aplica
5th rowNo aplica
ValueCountFrequency (%)
no 462530
47.8%
aplica 462530
47.8%
bogotá 9934
 
1.0%
cali 1757
 
0.2%
medellín 1477
 
0.2%
bucaramanga 973
 
0.1%
manizales 826
 
0.1%
cartagena 823
 
0.1%
villavicencio 764
 
0.1%
ibagué 729
 
0.1%
Other values (503) 24359
 
2.5%
2024-01-11T20:41:03.403736image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 964740
21.7%
o 493433
11.1%
l 477663
10.8%
i 477052
10.7%
c 470210
10.6%
466702
10.5%
p 464981
10.5%
N 463373
10.4%
t 16427
 
0.4%
e 15514
 
0.3%
Other values (45) 132860
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3472081
78.1%
Uppercase Letter 504172
 
11.3%
Space Separator 466702
 
10.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 964740
27.8%
o 493433
14.2%
l 477663
13.8%
i 477052
13.7%
c 470210
13.5%
p 464981
13.4%
t 16427
 
0.5%
e 15514
 
0.4%
g 14279
 
0.4%
n 13489
 
0.4%
Other values (20) 64293
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
N 463373
91.9%
B 12405
 
2.5%
C 5151
 
1.0%
M 4002
 
0.8%
P 3184
 
0.6%
S 2712
 
0.5%
A 2022
 
0.4%
V 1844
 
0.4%
T 1395
 
0.3%
D 1072
 
0.2%
Other values (14) 7012
 
1.4%
Space Separator
ValueCountFrequency (%)
466702
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3976253
89.5%
Common 466702
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 964740
24.3%
o 493433
12.4%
l 477663
12.0%
i 477052
12.0%
c 470210
11.8%
p 464981
11.7%
N 463373
11.7%
t 16427
 
0.4%
e 15514
 
0.4%
g 14279
 
0.4%
Other values (44) 118581
 
3.0%
Common
ValueCountFrequency (%)
466702
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4425211
99.6%
None 17744
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 964740
21.8%
o 493433
11.2%
l 477663
10.8%
i 477052
10.8%
c 470210
10.6%
466702
10.5%
p 464981
10.5%
N 463373
10.5%
t 16427
 
0.4%
e 15514
 
0.4%
Other values (37) 115116
 
2.6%
None
ValueCountFrequency (%)
á 11395
64.2%
í 2931
 
16.5%
é 1180
 
6.7%
ó 980
 
5.5%
ú 710
 
4.0%
ñ 521
 
2.9%
Á 18
 
0.1%
ü 9
 
0.1%

Fecha Adjudicacion
Text

MISSING 

Distinct2256
Distinct (%)4.9%
Missing454018
Missing (%)90.8%
Memory size7.6 MiB
2024-01-11T20:41:03.587215image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters459820
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique231 ?
Unique (%)0.5%

Sample

1st row06/29/2018
2nd row07/14/2022
3rd row07/12/2022
4th row09/21/2023
5th row04/13/2018
ValueCountFrequency (%)
06/28/2023 108
 
0.2%
11/12/2021 95
 
0.2%
12/15/2022 86
 
0.2%
11/13/2021 85
 
0.2%
03/30/2023 82
 
0.2%
12/07/2022 81
 
0.2%
12/16/2022 81
 
0.2%
12/23/2022 78
 
0.2%
06/29/2023 78
 
0.2%
11/17/2021 76
 
0.2%
Other values (2246) 45132
98.2%
2024-01-11T20:41:03.848806image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 117161
25.5%
0 104276
22.7%
/ 91964
20.0%
1 62756
13.6%
3 19562
 
4.3%
9 13998
 
3.0%
8 13719
 
3.0%
7 11535
 
2.5%
6 9014
 
2.0%
5 8058
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 367856
80.0%
Other Punctuation 91964
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 117161
31.8%
0 104276
28.3%
1 62756
17.1%
3 19562
 
5.3%
9 13998
 
3.8%
8 13719
 
3.7%
7 11535
 
3.1%
6 9014
 
2.5%
5 8058
 
2.2%
4 7777
 
2.1%
Other Punctuation
ValueCountFrequency (%)
/ 91964
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 459820
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 117161
25.5%
0 104276
22.7%
/ 91964
20.0%
1 62756
13.6%
3 19562
 
4.3%
9 13998
 
3.0%
8 13719
 
3.0%
7 11535
 
2.5%
6 9014
 
2.0%
5 8058
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 459820
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 117161
25.5%
0 104276
22.7%
/ 91964
20.0%
1 62756
13.6%
3 19562
 
4.3%
9 13998
 
3.0%
8 13719
 
3.0%
7 11535
 
2.5%
6 9014
 
2.0%
5 8058
 
1.8%

Valor Total Adjudicacion
Real number (ℝ)

SKEWED  ZEROS 

Distinct33703
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.488735816 × 1011
Minimum0
Maximum2.739481056 × 1017
Zeros454317
Zeros (%)90.9%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:03.936770image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile32692661.2
Maximum2.739481056 × 1017
Range2.739481056 × 1017
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.874213939 × 1014
Coefficient of variation (CV)705.848135
Kurtosis499998.6116
Mean5.488735816 × 1011
Median Absolute Deviation (MAD)0
Skewness707.1053096
Sum2.744367908 × 1017
Variance1.500953365 × 1029
MonotonicityNot monotonic
2024-01-11T20:41:04.003872image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 454317
90.9%
20000000 341
 
0.1%
10000000 308
 
0.1%
30000000 296
 
0.1%
50000000 249
 
< 0.1%
15000000 248
 
< 0.1%
40000000 229
 
< 0.1%
60000000 186
 
< 0.1%
25000000 173
 
< 0.1%
100000000 171
 
< 0.1%
Other values (33693) 43482
 
8.7%
ValueCountFrequency (%)
0 454317
90.9%
1 40
 
< 0.1%
2 5
 
< 0.1%
3 4
 
< 0.1%
4 7
 
< 0.1%
ValueCountFrequency (%)
2.739481056 × 10171
< 0.1%
3.1345552 × 10141
< 0.1%
6.985573974 × 10131
< 0.1%
3.1625 × 10131
< 0.1%
5.0802 × 10121
< 0.1%
Distinct10489
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:04.206497image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length80
Median length13
Mean length14.206546
Min length3

Characters and Unicode

Total characters7103273
Distinct characters84
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3703 ?
Unique (%)0.7%

Sample

1st rowNo Adjudicado
2nd rowNo Adjudicado
3rd rowNo Adjudicado
4th rowNo Adjudicado
5th rowNo Adjudicado
ValueCountFrequency (%)
no 454171
42.1%
adjudicado 454049
42.1%
maria 2237
 
0.2%
andres 1885
 
0.2%
de 1692
 
0.2%
juan 1362
 
0.1%
rodriguez 1330
 
0.1%
rojas 1141
 
0.1%
carlos 1130
 
0.1%
luis 998
 
0.1%
Other values (5438) 159341
 
14.8%
2024-01-11T20:41:04.517004image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 1371220
19.3%
o 929231
13.1%
A 590328
8.3%
579946
8.2%
N 511487
 
7.2%
a 496598
 
7.0%
i 473671
 
6.7%
u 461613
 
6.5%
c 459363
 
6.5%
j 455557
 
6.4%
Other values (74) 774259
10.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4779282
67.3%
Uppercase Letter 1743513
 
24.5%
Space Separator 579946
 
8.2%
Decimal Number 532
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 590328
33.9%
N 511487
29.3%
E 78820
 
4.5%
R 78471
 
4.5%
O 63016
 
3.6%
I 58934
 
3.4%
L 50728
 
2.9%
S 37968
 
2.2%
D 33602
 
1.9%
C 30980
 
1.8%
Other values (27) 209179
 
12.0%
Lowercase Letter
ValueCountFrequency (%)
d 1371220
28.7%
o 929231
19.4%
a 496598
 
10.4%
i 473671
 
9.9%
u 461613
 
9.7%
c 459363
 
9.6%
j 455557
 
9.5%
r 23803
 
0.5%
e 23751
 
0.5%
n 18643
 
0.4%
Other values (26) 65832
 
1.4%
Decimal Number
ValueCountFrequency (%)
2 146
27.4%
1 140
26.3%
8 67
12.6%
0 59
11.1%
7 28
 
5.3%
9 25
 
4.7%
3 19
 
3.6%
4 19
 
3.6%
6 15
 
2.8%
5 14
 
2.6%
Space Separator
ValueCountFrequency (%)
579946
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6522795
91.8%
Common 580478
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 1371220
21.0%
o 929231
14.2%
A 590328
9.1%
N 511487
 
7.8%
a 496598
 
7.6%
i 473671
 
7.3%
u 461613
 
7.1%
c 459363
 
7.0%
j 455557
 
7.0%
E 78820
 
1.2%
Other values (63) 694907
10.7%
Common
ValueCountFrequency (%)
579946
99.9%
2 146
 
< 0.1%
1 140
 
< 0.1%
8 67
 
< 0.1%
0 59
 
< 0.1%
7 28
 
< 0.1%
9 25
 
< 0.1%
3 19
 
< 0.1%
4 19
 
< 0.1%
6 15
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7093508
99.9%
None 9765
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 1371220
19.3%
o 929231
13.1%
A 590328
8.3%
579946
8.2%
N 511487
 
7.2%
a 496598
 
7.0%
i 473671
 
6.7%
u 461613
 
6.5%
c 459363
 
6.5%
j 455557
 
6.4%
Other values (53) 764494
10.8%
None
ValueCountFrequency (%)
Ñ 2905
29.7%
ñ 1039
 
10.6%
í 1000
 
10.2%
Ó 791
 
8.1%
á 730
 
7.5%
Á 709
 
7.3%
ó 663
 
6.8%
Í 626
 
6.4%
é 555
 
5.7%
É 387
 
4.0%
Other values (11) 360
 
3.7%
Distinct20325
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:04.738315image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length148
Median length13
Mean length14.22164
Min length6

Characters and Unicode

Total characters7110820
Distinct characters85
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13841 ?
Unique (%)2.8%

Sample

1st rowNo Adjudicado
2nd rowNo Adjudicado
3rd rowNo Adjudicado
4th rowNo Adjudicado
5th rowNo Adjudicado
ValueCountFrequency (%)
no 456316
42.1%
adjudicado 454049
41.9%
sas 18920
 
1.7%
de 8248
 
0.8%
y 4478
 
0.4%
sa 2621
 
0.2%
colombia 2327
 
0.2%
definido 2265
 
0.2%
ltda 2039
 
0.2%
del 1772
 
0.2%
Other values (16542) 131606
 
12.1%
2024-01-11T20:41:05.044051image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 1370932
19.3%
o 927189
13.0%
586779
8.3%
A 572527
8.1%
N 510435
 
7.2%
a 472683
 
6.6%
i 472382
 
6.6%
c 460203
 
6.5%
u 458924
 
6.5%
j 454601
 
6.4%
Other values (75) 824165
11.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4703668
66.1%
Uppercase Letter 1815099
 
25.5%
Space Separator 586779
 
8.3%
Decimal Number 5274
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 1370932
29.1%
o 927189
19.7%
a 472683
 
10.0%
i 472382
 
10.0%
c 460203
 
9.8%
u 458924
 
9.8%
j 454601
 
9.7%
e 16974
 
0.4%
n 12633
 
0.3%
r 12130
 
0.3%
Other values (27) 45017
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
A 572527
31.5%
N 510435
28.1%
S 99221
 
5.5%
E 80677
 
4.4%
I 80119
 
4.4%
O 79045
 
4.4%
R 64050
 
3.5%
C 52269
 
2.9%
L 44074
 
2.4%
T 37989
 
2.1%
Other values (27) 194693
 
10.7%
Decimal Number
ValueCountFrequency (%)
2 2272
43.1%
0 1369
26.0%
1 645
 
12.2%
3 404
 
7.7%
9 164
 
3.1%
8 111
 
2.1%
7 83
 
1.6%
5 79
 
1.5%
6 76
 
1.4%
4 71
 
1.3%
Space Separator
ValueCountFrequency (%)
586779
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6518767
91.7%
Common 592053
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 1370932
21.0%
o 927189
14.2%
A 572527
8.8%
N 510435
 
7.8%
a 472683
 
7.3%
i 472382
 
7.2%
c 460203
 
7.1%
u 458924
 
7.0%
j 454601
 
7.0%
S 99221
 
1.5%
Other values (64) 719670
11.0%
Common
ValueCountFrequency (%)
586779
99.1%
2 2272
 
0.4%
0 1369
 
0.2%
1 645
 
0.1%
3 404
 
0.1%
9 164
 
< 0.1%
8 111
 
< 0.1%
7 83
 
< 0.1%
5 79
 
< 0.1%
6 76
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7104347
99.9%
None 6473
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 1370932
19.3%
o 927189
13.1%
586779
8.3%
A 572527
8.1%
N 510435
 
7.2%
a 472683
 
6.7%
i 472382
 
6.6%
c 460203
 
6.5%
u 458924
 
6.5%
j 454601
 
6.4%
Other values (53) 817692
11.5%
None
ValueCountFrequency (%)
Ó 1585
24.5%
Ñ 1449
22.4%
Í 940
14.5%
ó 848
13.1%
í 455
 
7.0%
ñ 272
 
4.2%
É 251
 
3.9%
Á 210
 
3.2%
á 161
 
2.5%
é 149
 
2.3%
Other values (12) 153
 
2.4%
Distinct2676
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:05.239567image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length32
Median length13
Mean length12.80806
Min length8

Characters and Unicode

Total characters6404030
Distinct characters49
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2130 ?
Unique (%)0.4%

Sample

1st rowNo Adjudicado
2nd rowNo Adjudicado
3rd rowNo Adjudicado
4th rowNo Adjudicado
5th rowNo Adjudicado
ValueCountFrequency (%)
no 495880
49.8%
adjudicado 454049
45.6%
definido 41829
 
4.2%
1102720365 30
 
< 0.1%
8000181658 29
 
< 0.1%
8600077389 20
 
< 0.1%
1016018644 20
 
< 0.1%
9004466481 18
 
< 0.1%
8909000825 17
 
< 0.1%
1012374090 17
 
< 0.1%
Other values (2679) 3984
 
0.4%
2024-01-11T20:41:05.490683image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 1403977
21.9%
o 991762
15.5%
i 537711
 
8.4%
495893
 
7.7%
N 495883
 
7.7%
A 454062
 
7.1%
u 454051
 
7.1%
c 454051
 
7.1%
a 454051
 
7.1%
j 454049
 
7.1%
Other values (39) 208540
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4875154
76.1%
Uppercase Letter 991860
 
15.5%
Space Separator 495893
 
7.7%
Decimal Number 41123
 
0.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 495883
50.0%
A 454062
45.8%
D 41833
 
4.2%
S 15
 
< 0.1%
C 9
 
< 0.1%
E 8
 
< 0.1%
R 7
 
< 0.1%
I 7
 
< 0.1%
O 7
 
< 0.1%
U 5
 
< 0.1%
Other values (12) 24
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
d 1403977
28.8%
o 991762
20.3%
i 537711
 
11.0%
u 454051
 
9.3%
c 454051
 
9.3%
a 454051
 
9.3%
j 454049
 
9.3%
n 41833
 
0.9%
e 41830
 
0.9%
f 41829
 
0.9%
Other values (6) 10
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 8117
19.7%
1 6788
16.5%
9 4218
10.3%
8 3775
9.2%
2 3324
8.1%
3 3231
 
7.9%
6 2990
 
7.3%
7 2981
 
7.2%
5 2857
 
6.9%
4 2842
 
6.9%
Space Separator
ValueCountFrequency (%)
495893
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5867014
91.6%
Common 537016
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 1403977
23.9%
o 991762
16.9%
i 537711
 
9.2%
N 495883
 
8.5%
A 454062
 
7.7%
u 454051
 
7.7%
c 454051
 
7.7%
a 454051
 
7.7%
j 454049
 
7.7%
n 41833
 
0.7%
Other values (28) 125584
 
2.1%
Common
ValueCountFrequency (%)
495893
92.3%
0 8117
 
1.5%
1 6788
 
1.3%
9 4218
 
0.8%
8 3775
 
0.7%
2 3324
 
0.6%
3 3231
 
0.6%
6 2990
 
0.6%
7 2981
 
0.6%
5 2857
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6404030
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 1403977
21.9%
o 991762
15.5%
i 537711
 
8.4%
495893
 
7.7%
N 495883
 
7.7%
A 454062
 
7.1%
u 454051
 
7.1%
c 454051
 
7.1%
a 454051
 
7.1%
j 454049
 
7.1%
Other values (39) 208540
 
3.3%
Distinct9222
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:05.697093image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters5500000
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3074 ?
Unique (%)0.6%

Sample

1st rowV1.80161500
2nd rowV1.80111600
3rd rowV1.80111500
4th rowV1.86101705
5th rowV1.85101700
ValueCountFrequency (%)
v1.80111600 125328
25.1%
v1.80111701 28830
 
5.8%
v1.80111500 23854
 
4.8%
v1.80111620 20522
 
4.1%
v1.85101600 13833
 
2.8%
v1.80111601 10611
 
2.1%
v1.80111501 10371
 
2.1%
v1.80161500 10064
 
2.0%
v1.85101601 5337
 
1.1%
v1.80101500 4431
 
0.9%
Other values (9212) 246819
49.4%
2024-01-11T20:41:05.972095image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1865246
33.9%
0 1172174
21.3%
V 499999
 
9.1%
. 499999
 
9.1%
8 401871
 
7.3%
6 282035
 
5.1%
5 232215
 
4.2%
2 167892
 
3.1%
7 129673
 
2.4%
4 103476
 
1.9%
Other values (11) 145420
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4499991
81.8%
Uppercase Letter 500010
 
9.1%
Other Punctuation 499999
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1865246
41.4%
0 1172174
26.0%
8 401871
 
8.9%
6 282035
 
6.3%
5 232215
 
5.2%
2 167892
 
3.7%
7 129673
 
2.9%
4 103476
 
2.3%
3 90992
 
2.0%
9 54417
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
V 499999
> 99.9%
E 2
 
< 0.1%
I 2
 
< 0.1%
U 1
 
< 0.1%
N 1
 
< 0.1%
S 1
 
< 0.1%
P 1
 
< 0.1%
C 1
 
< 0.1%
F 1
 
< 0.1%
D 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 499999
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4999990
90.9%
Latin 500010
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1865246
37.3%
0 1172174
23.4%
. 499999
 
10.0%
8 401871
 
8.0%
6 282035
 
5.6%
5 232215
 
4.6%
2 167892
 
3.4%
7 129673
 
2.6%
4 103476
 
2.1%
3 90992
 
1.8%
Latin
ValueCountFrequency (%)
V 499999
> 99.9%
E 2
 
< 0.1%
I 2
 
< 0.1%
U 1
 
< 0.1%
N 1
 
< 0.1%
S 1
 
< 0.1%
P 1
 
< 0.1%
C 1
 
< 0.1%
F 1
 
< 0.1%
D 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5500000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1865246
33.9%
0 1172174
21.3%
V 499999
 
9.1%
. 499999
 
9.1%
8 401871
 
7.3%
6 282035
 
5.1%
5 232215
 
4.2%
2 167892
 
3.1%
7 129673
 
2.4%
4 103476
 
1.9%
Other values (11) 145420
 
2.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:06.060261image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3500000
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAbierto
2nd rowAbierto
3rd rowAbierto
4th rowAbierto
5th rowAbierto
ValueCountFrequency (%)
abierto 443220
88.6%
cerrado 56780
 
11.4%
2024-01-11T20:41:06.190589image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 556780
15.9%
e 500000
14.3%
o 500000
14.3%
A 443220
12.7%
b 443220
12.7%
i 443220
12.7%
t 443220
12.7%
C 56780
 
1.6%
a 56780
 
1.6%
d 56780
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3000000
85.7%
Uppercase Letter 500000
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 556780
18.6%
e 500000
16.7%
o 500000
16.7%
b 443220
14.8%
i 443220
14.8%
t 443220
14.8%
a 56780
 
1.9%
d 56780
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
A 443220
88.6%
C 56780
 
11.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 3500000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 556780
15.9%
e 500000
14.3%
o 500000
14.3%
A 443220
12.7%
b 443220
12.7%
i 443220
12.7%
t 443220
12.7%
C 56780
 
1.6%
a 56780
 
1.6%
d 56780
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 556780
15.9%
e 500000
14.3%
o 500000
14.3%
A 443220
12.7%
b 443220
12.7%
i 443220
12.7%
t 443220
12.7%
C 56780
 
1.6%
a 56780
 
1.6%
d 56780
 
1.6%
Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:06.290622image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length30
Median length30
Mean length25.143656
Min length2

Characters and Unicode

Total characters12571828
Distinct characters38
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowServicios de aprovisionamiento
2nd rowServicios de aprovisionamiento
3rd rowServicios de aprovisionamiento
4th rowServicios de aprovisionamiento
5th rowServicios de aprovisionamiento
ValueCountFrequency (%)
de 402546
28.3%
servicios 368822
26.0%
aprovisionamiento 347492
24.4%
decreto 51524
 
3.6%
092 51524
 
3.6%
2017 51524
 
3.6%
suministros 31221
 
2.2%
27 21330
 
1.5%
21330
 
1.5%
otros 21330
 
1.5%
Other values (18) 52605
 
3.7%
2024-01-11T20:41:06.456801image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1857002
14.8%
o 1547061
12.3%
e 1254090
10.0%
921248
 
7.3%
r 857321
 
6.8%
s 828474
 
6.6%
n 750309
 
6.0%
a 743428
 
5.9%
v 735968
 
5.9%
t 476168
 
3.8%
Other values (28) 2600759
20.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10712520
85.2%
Space Separator 921248
 
7.3%
Uppercase Letter 513402
 
4.1%
Decimal Number 403328
 
3.2%
Dash Punctuation 21330
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1857002
17.3%
o 1547061
14.4%
e 1254090
11.7%
r 857321
8.0%
s 828474
7.7%
n 750309
7.0%
a 743428
6.9%
v 735968
 
6.9%
t 476168
 
4.4%
c 424247
 
4.0%
Other values (11) 1238452
11.6%
Uppercase Letter
ValueCountFrequency (%)
S 380173
74.0%
D 64284
 
12.5%
O 29084
 
5.7%
C 20411
 
4.0%
N 12770
 
2.5%
A 4098
 
0.8%
I 1876
 
0.4%
M 632
 
0.1%
V 64
 
< 0.1%
E 10
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 124378
30.8%
0 103048
25.5%
7 72854
18.1%
1 51524
12.8%
9 51524
12.8%
Space Separator
ValueCountFrequency (%)
921248
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21330
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11225922
89.3%
Common 1345906
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 1857002
16.5%
o 1547061
13.8%
e 1254090
11.2%
r 857321
7.6%
s 828474
7.4%
n 750309
6.7%
a 743428
6.6%
v 735968
 
6.6%
t 476168
 
4.2%
c 424247
 
3.8%
Other values (21) 1751854
15.6%
Common
ValueCountFrequency (%)
921248
68.4%
2 124378
 
9.2%
0 103048
 
7.7%
7 72854
 
5.4%
1 51524
 
3.8%
9 51524
 
3.8%
- 21330
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12568413
> 99.9%
None 3415
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 1857002
14.8%
o 1547061
12.3%
e 1254090
10.0%
921248
 
7.3%
r 857321
 
6.8%
s 828474
 
6.6%
n 750309
 
6.0%
a 743428
 
5.9%
v 735968
 
5.9%
t 476168
 
3.8%
Other values (26) 2597344
20.7%
None
ValueCountFrequency (%)
í 3334
97.6%
ó 81
 
2.4%

Subtipo de Contrato
Text

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:06.549493image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters7500000
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo Especificado
2nd rowNo Especificado
3rd rowNo Especificado
4th rowNo Especificado
5th rowNo Especificado
ValueCountFrequency (%)
no 500000
50.0%
especificado 500000
50.0%
2024-01-11T20:41:06.811175image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1000000
13.3%
c 1000000
13.3%
i 1000000
13.3%
N 500000
6.7%
500000
6.7%
E 500000
6.7%
s 500000
6.7%
p 500000
6.7%
e 500000
6.7%
f 500000
6.7%
Other values (2) 1000000
13.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6000000
80.0%
Uppercase Letter 1000000
 
13.3%
Space Separator 500000
 
6.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1000000
16.7%
c 1000000
16.7%
i 1000000
16.7%
s 500000
8.3%
p 500000
8.3%
e 500000
8.3%
f 500000
8.3%
a 500000
8.3%
d 500000
8.3%
Uppercase Letter
ValueCountFrequency (%)
N 500000
50.0%
E 500000
50.0%
Space Separator
ValueCountFrequency (%)
500000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7000000
93.3%
Common 500000
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1000000
14.3%
c 1000000
14.3%
i 1000000
14.3%
N 500000
7.1%
E 500000
7.1%
s 500000
7.1%
p 500000
7.1%
e 500000
7.1%
f 500000
7.1%
a 500000
7.1%
Common
ValueCountFrequency (%)
500000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7500000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1000000
13.3%
c 1000000
13.3%
i 1000000
13.3%
N 500000
6.7%
500000
6.7%
E 500000
6.7%
s 500000
6.7%
p 500000
6.7%
e 500000
6.7%
f 500000
6.7%
Other values (2) 1000000
13.3%
Distinct30252
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:06.960241image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length500
Median length2
Mean length7.418436
Min length2

Characters and Unicode

Total characters3709218
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24869 ?
Unique (%)5.0%

Sample

1st rowND
2nd rowND
3rd rowND
4th rowND
5th rowND
ValueCountFrequency (%)
nd 438633
62.5%
v180111600 4375
 
0.6%
v180111700 2081
 
0.3%
v180101600 1636
 
0.2%
v181101500 1589
 
0.2%
v172103300 1197
 
0.2%
v180161500 1159
 
0.2%
v172102900 1055
 
0.2%
v180111620 1050
 
0.1%
v172101500 951
 
0.1%
Other values (15553) 248281
35.4%
2024-01-11T20:41:07.212787image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 863481
23.3%
0 498069
13.4%
N 438633
11.8%
D 438633
11.8%
V 263374
 
7.1%
2 221974
 
6.0%
202007
 
5.4%
5 159935
 
4.3%
4 150900
 
4.1%
3 117197
 
3.2%
Other values (4) 355015
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2366571
63.8%
Uppercase Letter 1140640
30.8%
Space Separator 202007
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 863481
36.5%
0 498069
21.0%
2 221974
 
9.4%
5 159935
 
6.8%
4 150900
 
6.4%
3 117197
 
5.0%
6 102973
 
4.4%
7 100516
 
4.2%
8 99571
 
4.2%
9 51955
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
N 438633
38.5%
D 438633
38.5%
V 263374
23.1%
Space Separator
ValueCountFrequency (%)
202007
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2568578
69.2%
Latin 1140640
30.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 863481
33.6%
0 498069
19.4%
2 221974
 
8.6%
202007
 
7.9%
5 159935
 
6.2%
4 150900
 
5.9%
3 117197
 
4.6%
6 102973
 
4.0%
7 100516
 
3.9%
8 99571
 
3.9%
Latin
ValueCountFrequency (%)
N 438633
38.5%
D 438633
38.5%
V 263374
23.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3709218
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 863481
23.3%
0 498069
13.4%
N 438633
11.8%
D 438633
11.8%
V 263374
 
7.1%
2 221974
 
6.0%
202007
 
5.4%
5 159935
 
4.3%
4 150900
 
4.1%
3 117197
 
3.2%
Other values (4) 355015
9.6%
Distinct498364
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:07.548041image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length149
Median length149
Mean length148.801466
Min length52

Characters and Unicode

Total characters74400733
Distinct characters51
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique497629 ?
Unique (%)99.5%

Sample

1st rowhttps://community.secop.gov.co/Public/Tendering/OpportunityDetail/Index?noticeUID=CO1.NTC.281797&isFromPublicArea=True&isModal=true&asPopupView=true
2nd rowhttps://community.secop.gov.co/Public/Tendering/OpportunityDetail/Index?noticeUID=CO1.NTC.2473286&isFromPublicArea=True&isModal=true&asPopupView=true
3rd rowhttps://community.secop.gov.co/Public/Tendering/OpportunityDetail/Index?noticeUID=CO1.NTC.1703723&isFromPublicArea=True&isModal=true&asPopupView=true
4th rowhttps://community.secop.gov.co/Public/Tendering/OpportunityDetail/Index?noticeUID=CO1.NTC.4477931&isFromPublicArea=True&isModal=true&asPopupView=true
5th rowhttps://community.secop.gov.co/Public/Tendering/OpportunityDetail/Index?noticeUID=CO1.NTC.3765144&isFromPublicArea=True&isModal=true&asPopupView=true
ValueCountFrequency (%)
https://community.secop.gov.co/sts/users/login/index 515
 
0.1%
https://community.secop.gov.co/public/tendering/opportunitydetail/index?noticeuid=co1.ntc.3894252&isfrompublicarea=true&ismodal=true&aspopupview=true 19
 
< 0.1%
https://community.secop.gov.co/public/tendering/opportunitydetail/index?noticeuid=co1.ntc.749939&isfrompublicarea=true&ismodal=true&aspopupview=true 18
 
< 0.1%
https://community.secop.gov.co/public/tendering/opportunitydetail/index?noticeuid=co1.ntc.2836216&isfrompublicarea=true&ismodal=true&aspopupview=true 18
 
< 0.1%
https://community.secop.gov.co/public/tendering/opportunitydetail/index?noticeuid=co1.ntc.1204204&isfrompublicarea=true&ismodal=true&aspopupview=true 17
 
< 0.1%
https://community.secop.gov.co/public/tendering/opportunitydetail/index?noticeuid=co1.ntc.2245296&isfrompublicarea=true&ismodal=true&aspopupview=true 11
 
< 0.1%
https://community.secop.gov.co/public/tendering/opportunitydetail/index?noticeuid=co1.ntc.3354077&isfrompublicarea=true&ismodal=true&aspopupview=true 11
 
< 0.1%
https://community.secop.gov.co/public/tendering/opportunitydetail/index?noticeuid=co1.ntc.2852987&isfrompublicarea=true&ismodal=true&aspopupview=true 9
 
< 0.1%
https://community.secop.gov.co/public/tendering/opportunitydetail/index?noticeuid=co1.ntc.2990301&isfrompublicarea=true&ismodal=true&aspopupview=true 9
 
< 0.1%
https://community.secop.gov.co/public/tendering/opportunitydetail/index?noticeuid=co1.ntc.3147748&isfrompublicarea=true&ismodal=true&aspopupview=true 9
 
< 0.1%
Other values (498354) 499364
99.9%
2024-01-11T20:41:07.912850image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 5495880
 
7.4%
i 4995880
 
6.7%
o 4497940
 
6.0%
t 4496910
 
6.0%
u 3996395
 
5.4%
r 3496910
 
4.7%
/ 3000000
 
4.0%
c 2998455
 
4.0%
n 2998455
 
4.0%
p 2997940
 
4.0%
Other values (41) 35425968
47.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 50466525
67.8%
Uppercase Letter 9992790
 
13.4%
Other Punctuation 7996910
 
10.7%
Decimal Number 3946568
 
5.3%
Math Symbol 1997940
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5495880
10.9%
i 4995880
9.9%
o 4497940
 
8.9%
t 4496910
 
8.9%
u 3996395
 
7.9%
r 3496910
 
6.9%
c 2998455
 
5.9%
n 2998455
 
5.9%
p 2997940
 
5.9%
s 2499485
 
5.0%
Other values (11) 11992275
23.8%
Uppercase Letter
ValueCountFrequency (%)
T 1498970
15.0%
P 1498455
15.0%
I 999485
10.0%
C 998970
10.0%
O 998970
10.0%
D 998970
10.0%
U 500000
 
5.0%
N 499485
 
5.0%
V 499485
 
5.0%
M 499485
 
5.0%
Other values (4) 1000515
10.0%
Decimal Number
ValueCountFrequency (%)
1 904559
22.9%
3 421334
10.7%
4 416230
10.5%
2 403578
10.2%
5 320848
 
8.1%
0 312035
 
7.9%
6 300971
 
7.6%
7 299930
 
7.6%
8 285359
 
7.2%
9 281724
 
7.1%
Other Punctuation
ValueCountFrequency (%)
/ 3000000
37.5%
. 2498970
31.2%
& 1498455
18.7%
: 500000
 
6.3%
? 499485
 
6.2%
Math Symbol
ValueCountFrequency (%)
= 1997940
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60459315
81.3%
Common 13941418
 
18.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5495880
 
9.1%
i 4995880
 
8.3%
o 4497940
 
7.4%
t 4496910
 
7.4%
u 3996395
 
6.6%
r 3496910
 
5.8%
c 2998455
 
5.0%
n 2998455
 
5.0%
p 2997940
 
5.0%
s 2499485
 
4.1%
Other values (25) 21985065
36.4%
Common
ValueCountFrequency (%)
/ 3000000
21.5%
. 2498970
17.9%
= 1997940
14.3%
& 1498455
10.7%
1 904559
 
6.5%
: 500000
 
3.6%
? 499485
 
3.6%
3 421334
 
3.0%
4 416230
 
3.0%
2 403578
 
2.9%
Other values (6) 1800867
12.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74400733
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 5495880
 
7.4%
i 4995880
 
6.7%
o 4497940
 
6.0%
t 4496910
 
6.0%
u 3996395
 
5.4%
r 3496910
 
4.7%
/ 3000000
 
4.0%
c 2998455
 
4.0%
n 2998455
 
4.0%
p 2997940
 
4.0%
Other values (41) 35425968
47.6%

Codigo Entidad
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size7.6 MiB
Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
2024-01-11T20:41:08.015368image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Length

Max length43
Median length10
Mean length13.806312
Min length10

Characters and Unicode

Total characters6903156
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAdjudicado
2nd rowAdjudicado
3rd rowAdjudicado
4th rowAdjudicado
5th rowAdjudicado
ValueCountFrequency (%)
adjudicado 353364
44.1%
de 145921
18.2%
presentación 140433
 
17.5%
oferta 129525
 
16.2%
observaciones 10884
 
1.4%
manifestación 4388
 
0.5%
interés 4388
 
0.5%
menor 4388
 
0.5%
cuantía 4388
 
0.5%
ofertas 1039
 
0.1%
Other values (12) 2698
 
0.3%
2024-01-11T20:41:08.180283image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 1206616
17.5%
a 654420
9.5%
e 594256
 
8.6%
i 519878
 
7.5%
o 511533
 
7.4%
c 509493
 
7.4%
u 357873
 
5.2%
A 353364
 
5.1%
j 353364
 
5.1%
n 314559
 
4.6%
Other values (26) 1527800
22.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6083279
88.1%
Uppercase Letter 509506
 
7.4%
Space Separator 301416
 
4.4%
Open Punctuation 4447
 
0.1%
Close Punctuation 4447
 
0.1%
Dash Punctuation 61
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 1206616
19.8%
a 654420
10.8%
e 594256
9.8%
i 519878
8.5%
o 511533
8.4%
c 509493
8.4%
u 357873
 
5.9%
j 353364
 
5.8%
n 314559
 
5.2%
r 291007
 
4.8%
Other values (12) 770280
12.7%
Uppercase Letter
ValueCountFrequency (%)
A 353364
69.4%
P 140607
 
27.6%
M 8776
 
1.7%
C 4570
 
0.9%
F 1002
 
0.2%
D 507
 
0.1%
N 507
 
0.1%
E 111
 
< 0.1%
S 59
 
< 0.1%
O 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
301416
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4447
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4447
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6592785
95.5%
Common 310371
 
4.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 1206616
18.3%
a 654420
9.9%
e 594256
9.0%
i 519878
7.9%
o 511533
7.8%
c 509493
7.7%
u 357873
 
5.4%
A 353364
 
5.4%
j 353364
 
5.4%
n 314559
 
4.8%
Other values (22) 1217429
18.5%
Common
ValueCountFrequency (%)
301416
97.1%
( 4447
 
1.4%
) 4447
 
1.4%
- 61
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6749378
97.8%
None 153778
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 1206616
17.9%
a 654420
9.7%
e 594256
8.8%
i 519878
 
7.7%
o 511533
 
7.6%
c 509493
 
7.5%
u 357873
 
5.3%
A 353364
 
5.2%
j 353364
 
5.2%
n 314559
 
4.7%
Other values (23) 1374022
20.4%
None
ValueCountFrequency (%)
ó 144941
94.3%
é 4449
 
2.9%
í 4388
 
2.9%